目录
相关文章
ML之XGBoost：利用XGBoost算法对波士顿数据集回归预测(模型调参【2种方法，ShuffleSplit+GridSearchCV、TimeSeriesSplitGSCV】、模型评估)
ML之XGBoost：利用XGBoost算法对波士顿数据集回归预测(模型调参【2种方法，ShuffleSplit+GridSearchCV、TimeSeriesSplitGSCV】、模型评估)实现
利用XGBoost算法对波士顿数据集回归预测
T1、ShuffleSplit+GSCV模型调参
输出XGBR_GSCV模型最佳得分、最优参数：0.8630,{'learning_rate': 0.12, 'max_depth': 3, 'n_estimators': 200}
XGBR_Shuffle_GSCV time： 256.7015066994206
XGBoost Score value: 0.8536645272887292
XGBoost R2 value: 0.8536645272887292
XGBoost MAE value: 2.1987844654894246
XGBoost RMSE value: 3.368537070469827
1. 0.588111 (0.039989) with: {'learning_rate': 0.03, 'max_depth': 1, 'n_estimators': 50} 2. 0.745248 (0.039715) with: {'learning_rate': 0.03, 'max_depth': 1, 'n_estimators': 100} 3. 0.780673 (0.041418) with: {'learning_rate': 0.03, 'max_depth': 1, 'n_estimators': 150} 4. 0.794564 (0.045098) with: {'learning_rate': 0.03, 'max_depth': 1, 'n_estimators': 200} 5. 0.739650 (0.048542) with: {'learning_rate': 0.03, 'max_depth': 3, 'n_estimators': 50} 6. 0.827152 (0.051752) with: {'learning_rate': 0.03, 'max_depth': 3, 'n_estimators': 100} 7. 0.843543 (0.056119) with: {'learning_rate': 0.03, 'max_depth': 3, 'n_estimators': 150} 8. 0.849557 (0.055848) with: {'learning_rate': 0.03, 'max_depth': 3, 'n_estimators': 200} 9. 0.740037 (0.040934) with: {'learning_rate': 0.03, 'max_depth': 5, 'n_estimators': 50} 10. 0.826966 (0.045216) with: {'learning_rate': 0.03, 'max_depth': 5, 'n_estimators': 100} 11. 0.841845 (0.047665) with: {'learning_rate': 0.03, 'max_depth': 5, 'n_estimators': 150} 12. 0.845978 (0.047794) with: {'learning_rate': 0.03, 'max_depth': 5, 'n_estimators': 200} 13. 0.720503 (0.038676) with: {'learning_rate': 0.03, 'max_depth': 7, 'n_estimators': 50} 14. 0.798275 (0.047791) with: {'learning_rate': 0.03, 'max_depth': 7, 'n_estimators': 100} 15. 0.808659 (0.048699) with: {'learning_rate': 0.03, 'max_depth': 7, 'n_estimators': 150} 16. 0.812894 (0.047902) with: {'learning_rate': 0.03, 'max_depth': 7, 'n_estimators': 200} 17. 0.716254 (0.039716) with: {'learning_rate': 0.03, 'max_depth': 9, 'n_estimators': 50} 18. 0.795603 (0.049370) with: {'learning_rate': 0.03, 'max_depth': 9, 'n_estimators': 100} 19. 0.804215 (0.054399) with: {'learning_rate': 0.03, 'max_depth': 9, 'n_estimators': 150} 20. 0.806022 (0.054965) with: {'learning_rate': 0.03, 'max_depth': 9, 'n_estimators': 200} 21. 0.714920 (0.040201) with: {'learning_rate': 0.03, 'max_depth': 11, 'n_estimators': 50} 22. 0.796940 (0.043692) with: {'learning_rate': 0.03, 'max_depth': 11, 'n_estimators': 100} 23. 0.803563 (0.047487) with: {'learning_rate': 0.03, 'max_depth': 11, 'n_estimators': 150} 24. 0.805639 (0.049146) with: {'learning_rate': 0.03, 'max_depth': 11, 'n_estimators': 200} 25. 0.717114 (0.040552) with: {'learning_rate': 0.03, 'max_depth': 13, 'n_estimators': 50} 26. 0.798669 (0.044140) with: {'learning_rate': 0.03, 'max_depth': 13, 'n_estimators': 100} 27. 0.807001 (0.047485) with: {'learning_rate': 0.03, 'max_depth': 13, 'n_estimators': 150} 28. 0.808231 (0.048622) with: {'learning_rate': 0.03, 'max_depth': 13, 'n_estimators': 200} 29. 0.716787 (0.040747) with: {'learning_rate': 0.03, 'max_depth': 15, 'n_estimators': 50} 30. 0.800528 (0.042525) with: {'learning_rate': 0.03, 'max_depth': 15, 'n_estimators': 100} 31. 0.810075 (0.045364) with: {'learning_rate': 0.03, 'max_depth': 15, 'n_estimators': 150} 32. 0.810928 (0.047001) with: {'learning_rate': 0.03, 'max_depth': 15, 'n_estimators': 200} 33. 0.748057 (0.039107) with: {'learning_rate': 0.06, 'max_depth': 1, 'n_estimators': 50} 34. 0.796450 (0.044658) with: {'learning_rate': 0.06, 'max_depth': 1, 'n_estimators': 100} 35. 0.810749 (0.049107) with: {'learning_rate': 0.06, 'max_depth': 1, 'n_estimators': 150} 36. 0.818271 (0.049566) with: {'learning_rate': 0.06, 'max_depth': 1, 'n_estimators': 200} 37. 0.825470 (0.054236) with: {'learning_rate': 0.06, 'max_depth': 3, 'n_estimators': 50} 38. 0.847820 (0.057729) with: {'learning_rate': 0.06, 'max_depth': 3, 'n_estimators': 100} 39. 0.852501 (0.057970) with: {'learning_rate': 0.06, 'max_depth': 3, 'n_estimators': 150} 40. 0.855974 (0.057133) with: {'learning_rate': 0.06, 'max_depth': 3, 'n_estimators': 200} 41. 0.830130 (0.042166) with: {'learning_rate': 0.06, 'max_depth': 5, 'n_estimators': 50} 42. 0.848818 (0.043202) with: {'learning_rate': 0.06, 'max_depth': 5, 'n_estimators': 100} 43. 0.850634 (0.043955) with: {'learning_rate': 0.06, 'max_depth': 5, 'n_estimators': 150} 44. 0.850776 (0.044242) with: {'learning_rate': 0.06, 'max_depth': 5, 'n_estimators': 200} 45. 0.797091 (0.049104) with: {'learning_rate': 0.06, 'max_depth': 7, 'n_estimators': 50} 46. 0.811453 (0.050410) with: {'learning_rate': 0.06, 'max_depth': 7, 'n_estimators': 100} 47. 0.812925 (0.050391) with: {'learning_rate': 0.06, 'max_depth': 7, 'n_estimators': 150} 48. 0.813141 (0.050317) with: {'learning_rate': 0.06, 'max_depth': 7, 'n_estimators': 200} 49. 0.798523 (0.048830) with: {'learning_rate': 0.06, 'max_depth': 9, 'n_estimators': 50} 50. 0.807724 (0.053522) with: {'learning_rate': 0.06, 'max_depth': 9, 'n_estimators': 100} 51. 0.808858 (0.053694) with: {'learning_rate': 0.06, 'max_depth': 9, 'n_estimators': 150} 52. 0.809064 (0.053787) with: {'learning_rate': 0.06, 'max_depth': 9, 'n_estimators': 200} 53. 0.795488 (0.045973) with: {'learning_rate': 0.06, 'max_depth': 11, 'n_estimators': 50} 54. 0.803783 (0.051639) with: {'learning_rate': 0.06, 'max_depth': 11, 'n_estimators': 100} 55. 0.805366 (0.052070) with: {'learning_rate': 0.06, 'max_depth': 11, 'n_estimators': 150} 56. 0.805499 (0.052113) with: {'learning_rate': 0.06, 'max_depth': 11, 'n_estimators': 200} 57. 0.796173 (0.046698) with: {'learning_rate': 0.06, 'max_depth': 13, 'n_estimators': 50} 58. 0.806388 (0.050425) with: {'learning_rate': 0.06, 'max_depth': 13, 'n_estimators': 100} 59. 0.807511 (0.050917) with: {'learning_rate': 0.06, 'max_depth': 13, 'n_estimators': 150} 60. 0.807696 (0.050925) with: {'learning_rate': 0.06, 'max_depth': 13, 'n_estimators': 200} 61. 0.795853 (0.045518) with: {'learning_rate': 0.06, 'max_depth': 15, 'n_estimators': 50} 62. 0.805835 (0.048817) with: {'learning_rate': 0.06, 'max_depth': 15, 'n_estimators': 100} 63. 0.806752 (0.049863) with: {'learning_rate': 0.06, 'max_depth': 15, 'n_estimators': 150} 64. 0.806967 (0.049886) with: {'learning_rate': 0.06, 'max_depth': 15, 'n_estimators': 200} 65. 0.782405 (0.041673) with: {'learning_rate': 0.09, 'max_depth': 1, 'n_estimators': 50} 66. 0.810724 (0.050393) with: {'learning_rate': 0.09, 'max_depth': 1, 'n_estimators': 100} 67. 0.820115 (0.051026) with: {'learning_rate': 0.09, 'max_depth': 1, 'n_estimators': 150} 68. 0.825857 (0.051649) with: {'learning_rate': 0.09, 'max_depth': 1, 'n_estimators': 200} 69. 0.843458 (0.056602) with: {'learning_rate': 0.09, 'max_depth': 3, 'n_estimators': 50} 70. 0.855060 (0.056710) with: {'learning_rate': 0.09, 'max_depth': 3, 'n_estimators': 100} 71. 0.858793 (0.055724) with: {'learning_rate': 0.09, 'max_depth': 3, 'n_estimators': 150} 72. 0.860149 (0.055734) with: {'learning_rate': 0.09, 'max_depth': 3, 'n_estimators': 200} 73. 0.842437 (0.046911) with: {'learning_rate': 0.09, 'max_depth': 5, 'n_estimators': 50} 74. 0.849599 (0.045852) with: {'learning_rate': 0.09, 'max_depth': 5, 'n_estimators': 100} 75. 0.850152 (0.046078) with: {'learning_rate': 0.09, 'max_depth': 5, 'n_estimators': 150} 76. 0.849891 (0.046197) with: {'learning_rate': 0.09, 'max_depth': 5, 'n_estimators': 200} 77. 0.807907 (0.051134) with: {'learning_rate': 0.09, 'max_depth': 7, 'n_estimators': 50} 78. 0.810696 (0.051038) with: {'learning_rate': 0.09, 'max_depth': 7, 'n_estimators': 100} 79. 0.810941 (0.050779) with: {'learning_rate': 0.09, 'max_depth': 7, 'n_estimators': 150} 80. 0.810979 (0.050839) with: {'learning_rate': 0.09, 'max_depth': 7, 'n_estimators': 200} 81. 0.804573 (0.052898) with: {'learning_rate': 0.09, 'max_depth': 9, 'n_estimators': 50} 82. 0.809204 (0.053292) with: {'learning_rate': 0.09, 'max_depth': 9, 'n_estimators': 100} 83. 0.809325 (0.053303) with: {'learning_rate': 0.09, 'max_depth': 9, 'n_estimators': 150} 84. 0.809351 (0.053284) with: {'learning_rate': 0.09, 'max_depth': 9, 'n_estimators': 200} 85. 0.804379 (0.051647) with: {'learning_rate': 0.09, 'max_depth': 11, 'n_estimators': 50} 86. 0.807157 (0.053047) with: {'learning_rate': 0.09, 'max_depth': 11, 'n_estimators': 100} 87. 0.807332 (0.053061) with: {'learning_rate': 0.09, 'max_depth': 11, 'n_estimators': 150} 88. 0.807335 (0.053062) with: {'learning_rate': 0.09, 'max_depth': 11, 'n_estimators': 200} 89. 0.809283 (0.050355) with: {'learning_rate': 0.09, 'max_depth': 13, 'n_estimators': 50} 90. 0.812004 (0.052245) with: {'learning_rate': 0.09, 'max_depth': 13, 'n_estimators': 100} 91. 0.812156 (0.052289) with: {'learning_rate': 0.09, 'max_depth': 13, 'n_estimators': 150} 92. 0.812158 (0.052290) with: {'learning_rate': 0.09, 'max_depth': 13, 'n_estimators': 200} 93. 0.808697 (0.047241) with: {'learning_rate': 0.09, 'max_depth': 15, 'n_estimators': 50} 94. 0.811460 (0.049551) with: {'learning_rate': 0.09, 'max_depth': 15, 'n_estimators': 100} 95. 0.811645 (0.049603) with: {'learning_rate': 0.09, 'max_depth': 15, 'n_estimators': 150} 96. 0.811647 (0.049603) with: {'learning_rate': 0.09, 'max_depth': 15, 'n_estimators': 200} 97. 0.797008 (0.044026) with: {'learning_rate': 0.12, 'max_depth': 1, 'n_estimators': 50} 98. 0.819497 (0.048774) with: {'learning_rate': 0.12, 'max_depth': 1, 'n_estimators': 100} 99. 0.828557 (0.049254) with: {'learning_rate': 0.12, 'max_depth': 1, 'n_estimators': 150} 100. 0.831446 (0.048579) with: {'learning_rate': 0.12, 'max_depth': 1, 'n_estimators': 200} 101. 0.850108 (0.054443) with: {'learning_rate': 0.12, 'max_depth': 3, 'n_estimators': 50} 102. 0.860703 (0.051990) with: {'learning_rate': 0.12, 'max_depth': 3, 'n_estimators': 100} 103. 0.862097 (0.050875) with: {'learning_rate': 0.12, 'max_depth': 3, 'n_estimators': 150} 104. 0.862991 (0.050771) with: {'learning_rate': 0.12, 'max_depth': 3, 'n_estimators': 200} 105. 0.845629 (0.050619) with: {'learning_rate': 0.12, 'max_depth': 5, 'n_estimators': 50} 106. 0.846694 (0.051708) with: {'learning_rate': 0.12, 'max_depth': 5, 'n_estimators': 100} 107. 0.846881 (0.051518) with: {'learning_rate': 0.12, 'max_depth': 5, 'n_estimators': 150} 108. 0.847447 (0.051179) with: {'learning_rate': 0.12, 'max_depth': 5, 'n_estimators': 200} 109. 0.818390 (0.048416) with: {'learning_rate': 0.12, 'max_depth': 7, 'n_estimators': 50} 110. 0.820131 (0.048414) with: {'learning_rate': 0.12, 'max_depth': 7, 'n_estimators': 100} 111. 0.820054 (0.048396) with: {'learning_rate': 0.12, 'max_depth': 7, 'n_estimators': 150} 112. 0.820016 (0.048421) with: {'learning_rate': 0.12, 'max_depth': 7, 'n_estimators': 200} 113. 0.804340 (0.057268) with: {'learning_rate': 0.12, 'max_depth': 9, 'n_estimators': 50} 114. 0.806046 (0.057127) with: {'learning_rate': 0.12, 'max_depth': 9, 'n_estimators': 100} 115. 0.806095 (0.057104) with: {'learning_rate': 0.12, 'max_depth': 9, 'n_estimators': 150} 116. 0.806095 (0.057104) with: {'learning_rate': 0.12, 'max_depth': 9, 'n_estimators': 200} 117. 0.810022 (0.052949) with: {'learning_rate': 0.12, 'max_depth': 11, 'n_estimators': 50} 118. 0.810958 (0.053529) with: {'learning_rate': 0.12, 'max_depth': 11, 'n_estimators': 100} 119. 0.810963 (0.053537) with: {'learning_rate': 0.12, 'max_depth': 11, 'n_estimators': 150} 120. 0.810963 (0.053537) with: {'learning_rate': 0.12, 'max_depth': 11, 'n_estimators': 200} 121. 0.807990 (0.050201) with: {'learning_rate': 0.12, 'max_depth': 13, 'n_estimators': 50} 122. 0.809496 (0.050527) with: {'learning_rate': 0.12, 'max_depth': 13, 'n_estimators': 100} 123. 0.809512 (0.050529) with: {'learning_rate': 0.12, 'max_depth': 13, 'n_estimators': 150} 124. 0.809512 (0.050529) with: {'learning_rate': 0.12, 'max_depth': 13, 'n_estimators': 200} 125. 0.810050 (0.051373) with: {'learning_rate': 0.12, 'max_depth': 15, 'n_estimators': 50} 126. 0.811131 (0.052055) with: {'learning_rate': 0.12, 'max_depth': 15, 'n_estimators': 100} 127. 0.811146 (0.052061) with: {'learning_rate': 0.12, 'max_depth': 15, 'n_estimators': 150} 128. 0.811146 (0.052061) with: {'learning_rate': 0.12, 'max_depth': 15, 'n_estimators': 200} 129. 0.807162 (0.048547) with: {'learning_rate': 0.15, 'max_depth': 1, 'n_estimators': 50} 130. 0.824273 (0.050445) with: {'learning_rate': 0.15, 'max_depth': 1, 'n_estimators': 100} 131. 0.830500 (0.050552) with: {'learning_rate': 0.15, 'max_depth': 1, 'n_estimators': 150} 132. 0.830391 (0.051783) with: {'learning_rate': 0.15, 'max_depth': 1, 'n_estimators': 200} 133. 0.852195 (0.056525) with: {'learning_rate': 0.15, 'max_depth': 3, 'n_estimators': 50} 134. 0.858841 (0.055583) with: {'learning_rate': 0.15, 'max_depth': 3, 'n_estimators': 100} 135. 0.860678 (0.055755) with: {'learning_rate': 0.15, 'max_depth': 3, 'n_estimators': 150} 136. 0.860202 (0.056060) with: {'learning_rate': 0.15, 'max_depth': 3, 'n_estimators': 200} 137. 0.851480 (0.042938) with: {'learning_rate': 0.15, 'max_depth': 5, 'n_estimators': 50} 138. 0.852485 (0.043547) with: {'learning_rate': 0.15, 'max_depth': 5, 'n_estimators': 100} 139. 0.852983 (0.043729) with: {'learning_rate': 0.15, 'max_depth': 5, 'n_estimators': 150} 140. 0.853004 (0.043800) with: {'learning_rate': 0.15, 'max_depth': 5, 'n_estimators': 200} 141. 0.811017 (0.051230) with: {'learning_rate': 0.15, 'max_depth': 7, 'n_estimators': 50} 142. 0.811935 (0.051563) with: {'learning_rate': 0.15, 'max_depth': 7, 'n_estimators': 100} 143. 0.812016 (0.051550) with: {'learning_rate': 0.15, 'max_depth': 7, 'n_estimators': 150} 144. 0.812016 (0.051550) with: {'learning_rate': 0.15, 'max_depth': 7, 'n_estimators': 200} 145. 0.807335 (0.054503) with: {'learning_rate': 0.15, 'max_depth': 9, 'n_estimators': 50} 146. 0.807742 (0.054438) with: {'learning_rate': 0.15, 'max_depth': 9, 'n_estimators': 100} 147. 0.807742 (0.054438) with: {'learning_rate': 0.15, 'max_depth': 9, 'n_estimators': 150} 148. 0.807742 (0.054438) with: {'learning_rate': 0.15, 'max_depth': 9, 'n_estimators': 200} 149. 0.810597 (0.052285) with: {'learning_rate': 0.15, 'max_depth': 11, 'n_estimators': 50} 150. 0.810936 (0.052312) with: {'learning_rate': 0.15, 'max_depth': 11, 'n_estimators': 100} 151. 0.810936 (0.052312) with: {'learning_rate': 0.15, 'max_depth': 11, 'n_estimators': 150} 152. 0.810936 (0.052312) with: {'learning_rate': 0.15, 'max_depth': 11, 'n_estimators': 200} 153. 0.814041 (0.049302) with: {'learning_rate': 0.15, 'max_depth': 13, 'n_estimators': 50} 154. 0.814413 (0.049371) with: {'learning_rate': 0.15, 'max_depth': 13, 'n_estimators': 100} 155. 0.814413 (0.049371) with: {'learning_rate': 0.15, 'max_depth': 13, 'n_estimators': 150} 156. 0.814413 (0.049371) with: {'learning_rate': 0.15, 'max_depth': 13, 'n_estimators': 200} 157. 0.807168 (0.053947) with: {'learning_rate': 0.15, 'max_depth': 15, 'n_estimators': 50} 158. 0.807499 (0.054091) with: {'learning_rate': 0.15, 'max_depth': 15, 'n_estimators': 100} 159. 0.807499 (0.054091) with: {'learning_rate': 0.15, 'max_depth': 15, 'n_estimators': 150} 160. 0.807499 (0.054091) with: {'learning_rate': 0.15, 'max_depth': 15, 'n_estimators': 200} 161. 0.810923 (0.050566) with: {'learning_rate': 0.18, 'max_depth': 1, 'n_estimators': 50} 162. 0.826561 (0.050272) with: {'learning_rate': 0.18, 'max_depth': 1, 'n_estimators': 100} 163. 0.830294 (0.049726) with: {'learning_rate': 0.18, 'max_depth': 1, 'n_estimators': 150} 164. 0.830412 (0.050068) with: {'learning_rate': 0.18, 'max_depth': 1, 'n_estimators': 200} 165. 0.847566 (0.059016) with: {'learning_rate': 0.18, 'max_depth': 3, 'n_estimators': 50} 166. 0.854473 (0.056008) with: {'learning_rate': 0.18, 'max_depth': 3, 'n_estimators': 100} 167. 0.855668 (0.056143) with: {'learning_rate': 0.18, 'max_depth': 3, 'n_estimators': 150} 168. 0.855706 (0.055851) with: {'learning_rate': 0.18, 'max_depth': 3, 'n_estimators': 200} 169. 0.841307 (0.052664) with: {'learning_rate': 0.18, 'max_depth': 5, 'n_estimators': 50} 170. 0.841590 (0.053217) with: {'learning_rate': 0.18, 'max_depth': 5, 'n_estimators': 100} 171. 0.841445 (0.053423) with: {'learning_rate': 0.18, 'max_depth': 5, 'n_estimators': 150} 172. 0.841435 (0.053478) with: {'learning_rate': 0.18, 'max_depth': 5, 'n_estimators': 200} 173. 0.807878 (0.052757) with: {'learning_rate': 0.18, 'max_depth': 7, 'n_estimators': 50} 174. 0.808334 (0.052373) with: {'learning_rate': 0.18, 'max_depth': 7, 'n_estimators': 100} 175. 0.808363 (0.052378) with: {'learning_rate': 0.18, 'max_depth': 7, 'n_estimators': 150} 176. 0.808363 (0.052378) with: {'learning_rate': 0.18, 'max_depth': 7, 'n_estimators': 200} 177. 0.804948 (0.054592) with: {'learning_rate': 0.18, 'max_depth': 9, 'n_estimators': 50} 178. 0.805130 (0.054519) with: {'learning_rate': 0.18, 'max_depth': 9, 'n_estimators': 100} 179. 0.805130 (0.054519) with: {'learning_rate': 0.18, 'max_depth': 9, 'n_estimators': 150} 180. 0.805130 (0.054519) with: {'learning_rate': 0.18, 'max_depth': 9, 'n_estimators': 200} 181. 0.803086 (0.052977) with: {'learning_rate': 0.18, 'max_depth': 11, 'n_estimators': 50} 182. 0.803229 (0.052990) with: {'learning_rate': 0.18, 'max_depth': 11, 'n_estimators': 100} 183. 0.803229 (0.052990) with: {'learning_rate': 0.18, 'max_depth': 11, 'n_estimators': 150} 184. 0.803229 (0.052990) with: {'learning_rate': 0.18, 'max_depth': 11, 'n_estimators': 200} 185. 0.806149 (0.054086) with: {'learning_rate': 0.18, 'max_depth': 13, 'n_estimators': 50} 186. 0.806294 (0.054156) with: {'learning_rate': 0.18, 'max_depth': 13, 'n_estimators': 100} 187. 0.806294 (0.054156) with: {'learning_rate': 0.18, 'max_depth': 13, 'n_estimators': 150} 188. 0.806294 (0.054156) with: {'learning_rate': 0.18, 'max_depth': 13, 'n_estimators': 200} 189. 0.805339 (0.054438) with: {'learning_rate': 0.18, 'max_depth': 15, 'n_estimators': 50} 190. 0.805497 (0.054478) with: {'learning_rate': 0.18, 'max_depth': 15, 'n_estimators': 100} 191. 0.805497 (0.054478) with: {'learning_rate': 0.18, 'max_depth': 15, 'n_estimators': 150} 192. 0.805497 (0.054478) with: {'learning_rate': 0.18, 'max_depth': 15, 'n_estimators': 200} 193. 0.818772 (0.048965) with: {'learning_rate': 0.21, 'max_depth': 1, 'n_estimators': 50} 194. 0.830305 (0.048710) with: {'learning_rate': 0.21, 'max_depth': 1, 'n_estimators': 100} 195. 0.832875 (0.048551) with: {'learning_rate': 0.21, 'max_depth': 1, 'n_estimators': 150} 196. 0.833115 (0.049489) with: {'learning_rate': 0.21, 'max_depth': 1, 'n_estimators': 200} 197. 0.852619 (0.055268) with: {'learning_rate': 0.21, 'max_depth': 3, 'n_estimators': 50} 198. 0.854279 (0.055507) with: {'learning_rate': 0.21, 'max_depth': 3, 'n_estimators': 100} 199. 0.855926 (0.055786) with: {'learning_rate': 0.21, 'max_depth': 3, 'n_estimators': 150} 200. 0.857225 (0.055403) with: {'learning_rate': 0.21, 'max_depth': 3, 'n_estimators': 200} 201. 0.844948 (0.048417) with: {'learning_rate': 0.21, 'max_depth': 5, 'n_estimators': 50} 202. 0.844659 (0.048358) with: {'learning_rate': 0.21, 'max_depth': 5, 'n_estimators': 100} 203. 0.844761 (0.048342) with: {'learning_rate': 0.21, 'max_depth': 5, 'n_estimators': 150} 204. 0.844807 (0.048326) with: {'learning_rate': 0.21, 'max_depth': 5, 'n_estimators': 200} 205. 0.816587 (0.052132) with: {'learning_rate': 0.21, 'max_depth': 7, 'n_estimators': 50} 206. 0.816323 (0.052509) with: {'learning_rate': 0.21, 'max_depth': 7, 'n_estimators': 100} 207. 0.816322 (0.052509) with: {'learning_rate': 0.21, 'max_depth': 7, 'n_estimators': 150} 208. 0.816322 (0.052509) with: {'learning_rate': 0.21, 'max_depth': 7, 'n_estimators': 200} 209. 0.807687 (0.050865) with: {'learning_rate': 0.21, 'max_depth': 9, 'n_estimators': 50} 210. 0.807783 (0.050856) with: {'learning_rate': 0.21, 'max_depth': 9, 'n_estimators': 100} 211. 0.807783 (0.050856) with: {'learning_rate': 0.21, 'max_depth': 9, 'n_estimators': 150} 212. 0.807783 (0.050856) with: {'learning_rate': 0.21, 'max_depth': 9, 'n_estimators': 200} 213. 0.807752 (0.054800) with: {'learning_rate': 0.21, 'max_depth': 11, 'n_estimators': 50} 214. 0.807782 (0.054819) with: {'learning_rate': 0.21, 'max_depth': 11, 'n_estimators': 100} 215. 0.807782 (0.054819) with: {'learning_rate': 0.21, 'max_depth': 11, 'n_estimators': 150} 216. 0.807782 (0.054819) with: {'learning_rate': 0.21, 'max_depth': 11, 'n_estimators': 200} 217. 0.806377 (0.052411) with: {'learning_rate': 0.21, 'max_depth': 13, 'n_estimators': 50} 218. 0.806415 (0.052447) with: {'learning_rate': 0.21, 'max_depth': 13, 'n_estimators': 100} 219. 0.806415 (0.052447) with: {'learning_rate': 0.21, 'max_depth': 13, 'n_estimators': 150} 220. 0.806415 (0.052447) with: {'learning_rate': 0.21, 'max_depth': 13, 'n_estimators': 200} 221. 0.807638 (0.052222) with: {'learning_rate': 0.21, 'max_depth': 15, 'n_estimators': 50} 222. 0.807671 (0.052247) with: {'learning_rate': 0.21, 'max_depth': 15, 'n_estimators': 100} 223. 0.807671 (0.052247) with: {'learning_rate': 0.21, 'max_depth': 15, 'n_estimators': 150} 224. 0.807671 (0.052247) with: {'learning_rate': 0.21, 'max_depth': 15, 'n_estimators': 200} 225. 0.819971 (0.046487) with: {'learning_rate': 0.24, 'max_depth': 1, 'n_estimators': 50} 226. 0.830501 (0.048655) with: {'learning_rate': 0.24, 'max_depth': 1, 'n_estimators': 100} 227. 0.832064 (0.049740) with: {'learning_rate': 0.24, 'max_depth': 1, 'n_estimators': 150} 228. 0.831840 (0.050128) with: {'learning_rate': 0.24, 'max_depth': 1, 'n_estimators': 200} 229. 0.857136 (0.046683) with: {'learning_rate': 0.24, 'max_depth': 3, 'n_estimators': 50} 230. 0.859483 (0.045770) with: {'learning_rate': 0.24, 'max_depth': 3, 'n_estimators': 100} 231. 0.859945 (0.045322) with: {'learning_rate': 0.24, 'max_depth': 3, 'n_estimators': 150} 232. 0.859801 (0.045460) with: {'learning_rate': 0.24, 'max_depth': 3, 'n_estimators': 200} 233. 0.850955 (0.049845) with: {'learning_rate': 0.24, 'max_depth': 5, 'n_estimators': 50} 234. 0.850508 (0.050615) with: {'learning_rate': 0.24, 'max_depth': 5, 'n_estimators': 100} 235. 0.850476 (0.050598) with: {'learning_rate': 0.24, 'max_depth': 5, 'n_estimators': 150} 236. 0.850498 (0.050571) with: {'learning_rate': 0.24, 'max_depth': 5, 'n_estimators': 200} 237. 0.811733 (0.057462) with: {'learning_rate': 0.24, 'max_depth': 7, 'n_estimators': 50} 238. 0.811878 (0.057440) with: {'learning_rate': 0.24, 'max_depth': 7, 'n_estimators': 100} 239. 0.811878 (0.057440) with: {'learning_rate': 0.24, 'max_depth': 7, 'n_estimators': 150} 240. 0.811878 (0.057440) with: {'learning_rate': 0.24, 'max_depth': 7, 'n_estimators': 200} 241. 0.807850 (0.060428) with: {'learning_rate': 0.24, 'max_depth': 9, 'n_estimators': 50} 242. 0.807894 (0.060424) with: {'learning_rate': 0.24, 'max_depth': 9, 'n_estimators': 100} 243. 0.807894 (0.060424) with: {'learning_rate': 0.24, 'max_depth': 9, 'n_estimators': 150} 244. 0.807894 (0.060424) with: {'learning_rate': 0.24, 'max_depth': 9, 'n_estimators': 200} 245. 0.802244 (0.059772) with: {'learning_rate': 0.24, 'max_depth': 11, 'n_estimators': 50} 246. 0.802246 (0.059770) with: {'learning_rate': 0.24, 'max_depth': 11, 'n_estimators': 100} 247. 0.802246 (0.059770) with: {'learning_rate': 0.24, 'max_depth': 11, 'n_estimators': 150} 248. 0.802246 (0.059770) with: {'learning_rate': 0.24, 'max_depth': 11, 'n_estimators': 200} 249. 0.807033 (0.061863) with: {'learning_rate': 0.24, 'max_depth': 13, 'n_estimators': 50} 250. 0.807040 (0.061864) with: {'learning_rate': 0.24, 'max_depth': 13, 'n_estimators': 100} 251. 0.807040 (0.061864) with: {'learning_rate': 0.24, 'max_depth': 13, 'n_estimators': 150} 252. 0.807040 (0.061864) with: {'learning_rate': 0.24, 'max_depth': 13, 'n_estimators': 200} 253. 0.804463 (0.063512) with: {'learning_rate': 0.24, 'max_depth': 15, 'n_estimators': 50} 254. 0.804475 (0.063511) with: {'learning_rate': 0.24, 'max_depth': 15, 'n_estimators': 100} 255. 0.804475 (0.063511) with: {'learning_rate': 0.24, 'max_depth': 15, 'n_estimators': 150} 256. 0.804475 (0.063511) with: {'learning_rate': 0.24, 'max_depth': 15, 'n_estimators': 200} 257. 0.821150 (0.049890) with: {'learning_rate': 0.27, 'max_depth': 1, 'n_estimators': 50} 258. 0.830742 (0.049213) with: {'learning_rate': 0.27, 'max_depth': 1, 'n_estimators': 100} 259. 0.831787 (0.050679) with: {'learning_rate': 0.27, 'max_depth': 1, 'n_estimators': 150} 260. 0.830709 (0.051395) with: {'learning_rate': 0.27, 'max_depth': 1, 'n_estimators': 200} 261. 0.857873 (0.052985) with: {'learning_rate': 0.27, 'max_depth': 3, 'n_estimators': 50} 262. 0.861046 (0.050332) with: {'learning_rate': 0.27, 'max_depth': 3, 'n_estimators': 100} 263. 0.861720 (0.049712) with: {'learning_rate': 0.27, 'max_depth': 3, 'n_estimators': 150} 264. 0.861372 (0.049998) with: {'learning_rate': 0.27, 'max_depth': 3, 'n_estimators': 200} 265. 0.847206 (0.051159) with: {'learning_rate': 0.27, 'max_depth': 5, 'n_estimators': 50} 266. 0.847094 (0.051525) with: {'learning_rate': 0.27, 'max_depth': 5, 'n_estimators': 100} 267. 0.847037 (0.051513) with: {'learning_rate': 0.27, 'max_depth': 5, 'n_estimators': 150} 268. 0.847035 (0.051514) with: {'learning_rate': 0.27, 'max_depth': 5, 'n_estimators': 200} 269. 0.803202 (0.050403) with: {'learning_rate': 0.27, 'max_depth': 7, 'n_estimators': 50} 270. 0.803226 (0.050360) with: {'learning_rate': 0.27, 'max_depth': 7, 'n_estimators': 100} 271. 0.803226 (0.050360) with: {'learning_rate': 0.27, 'max_depth': 7, 'n_estimators': 150} 272. 0.803226 (0.050360) with: {'learning_rate': 0.27, 'max_depth': 7, 'n_estimators': 200} 273. 0.806931 (0.056619) with: {'learning_rate': 0.27, 'max_depth': 9, 'n_estimators': 50} 274. 0.806930 (0.056616) with: {'learning_rate': 0.27, 'max_depth': 9, 'n_estimators': 100} 275. 0.806930 (0.056616) with: {'learning_rate': 0.27, 'max_depth': 9, 'n_estimators': 150} 276. 0.806930 (0.056616) with: {'learning_rate': 0.27, 'max_depth': 9, 'n_estimators': 200} 277. 0.802898 (0.060888) with: {'learning_rate': 0.27, 'max_depth': 11, 'n_estimators': 50} 278. 0.802900 (0.060887) with: {'learning_rate': 0.27, 'max_depth': 11, 'n_estimators': 100} 279. 0.802900 (0.060887) with: {'learning_rate': 0.27, 'max_depth': 11, 'n_estimators': 150} 280. 0.802900 (0.060887) with: {'learning_rate': 0.27, 'max_depth': 11, 'n_estimators': 200} 281. 0.799887 (0.055534) with: {'learning_rate': 0.27, 'max_depth': 13, 'n_estimators': 50} 282. 0.799886 (0.055534) with: {'learning_rate': 0.27, 'max_depth': 13, 'n_estimators': 100} 283. 0.799886 (0.055534) with: {'learning_rate': 0.27, 'max_depth': 13, 'n_estimators': 150} 284. 0.799886 (0.055534) with: {'learning_rate': 0.27, 'max_depth': 13, 'n_estimators': 200} 285. 0.800050 (0.056070) with: {'learning_rate': 0.27, 'max_depth': 15, 'n_estimators': 50} 286. 0.800051 (0.056071) with: {'learning_rate': 0.27, 'max_depth': 15, 'n_estimators': 100} 287. 0.800051 (0.056071) with: {'learning_rate': 0.27, 'max_depth': 15, 'n_estimators': 150} 288. 0.800051 (0.056071) with: {'learning_rate': 0.27, 'max_depth': 15, 'n_estimators': 200} 289. 0.819760 (0.053159) with: {'learning_rate': 0.3, 'max_depth': 1, 'n_estimators': 50} 290. 0.827881 (0.052422) with: {'learning_rate': 0.3, 'max_depth': 1, 'n_estimators': 100} 291. 0.828890 (0.053188) with: {'learning_rate': 0.3, 'max_depth': 1, 'n_estimators': 150} 292. 0.829313 (0.052821) with: {'learning_rate': 0.3, 'max_depth': 1, 'n_estimators': 200} 293. 0.854570 (0.052578) with: {'learning_rate': 0.3, 'max_depth': 3, 'n_estimators': 50} 294. 0.857880 (0.050891) with: {'learning_rate': 0.3, 'max_depth': 3, 'n_estimators': 100} 295. 0.858274 (0.051601) with: {'learning_rate': 0.3, 'max_depth': 3, 'n_estimators': 150} 296. 0.858004 (0.051720) with: {'learning_rate': 0.3, 'max_depth': 3, 'n_estimators': 200} 297. 0.837382 (0.048349) with: {'learning_rate': 0.3, 'max_depth': 5, 'n_estimators': 50} 298. 0.837511 (0.048140) with: {'learning_rate': 0.3, 'max_depth': 5, 'n_estimators': 100} 299. 0.837538 (0.048128) with: {'learning_rate': 0.3, 'max_depth': 5, 'n_estimators': 150} 300. 0.837538 (0.048128) with: {'learning_rate': 0.3, 'max_depth': 5, 'n_estimators': 200} 301. 0.814336 (0.051179) with: {'learning_rate': 0.3, 'max_depth': 7, 'n_estimators': 50} 302. 0.814383 (0.051205) with: {'learning_rate': 0.3, 'max_depth': 7, 'n_estimators': 100} 303. 0.814383 (0.051205) with: {'learning_rate': 0.3, 'max_depth': 7, 'n_estimators': 150} 304. 0.814383 (0.051205) with: {'learning_rate': 0.3, 'max_depth': 7, 'n_estimators': 200} 305. 0.806069 (0.051545) with: {'learning_rate': 0.3, 'max_depth': 9, 'n_estimators': 50} 306. 0.806069 (0.051545) with: {'learning_rate': 0.3, 'max_depth': 9, 'n_estimators': 100} 307. 0.806069 (0.051545) with: {'learning_rate': 0.3, 'max_depth': 9, 'n_estimators': 150} 308. 0.806069 (0.051545) with: {'learning_rate': 0.3, 'max_depth': 9, 'n_estimators': 200} 309. 0.810698 (0.049687) with: {'learning_rate': 0.3, 'max_depth': 11, 'n_estimators': 50} 310. 0.810698 (0.049687) with: {'learning_rate': 0.3, 'max_depth': 11, 'n_estimators': 100} 311. 0.810698 (0.049687) with: {'learning_rate': 0.3, 'max_depth': 11, 'n_estimators': 150} 312. 0.810698 (0.049687) with: {'learning_rate': 0.3, 'max_depth': 11, 'n_estimators': 200} 313. 0.807420 (0.051992) with: {'learning_rate': 0.3, 'max_depth': 13, 'n_estimators': 50} 314. 0.807420 (0.051992) with: {'learning_rate': 0.3, 'max_depth': 13, 'n_estimators': 100} 315. 0.807420 (0.051992) with: {'learning_rate': 0.3, 'max_depth': 13, 'n_estimators': 150} 316. 0.807420 (0.051992) with: {'learning_rate': 0.3, 'max_depth': 13, 'n_estimators': 200} 317. 0.803384 (0.054540) with: {'learning_rate': 0.3, 'max_depth': 15, 'n_estimators': 50} 318. 0.803384 (0.054540) with: {'learning_rate': 0.3, 'max_depth': 15, 'n_estimators': 100} 319. 0.803384 (0.054540) with: {'learning_rate': 0.3, 'max_depth': 15, 'n_estimators': 150} 320. 0.803384 (0.054540) with: {'learning_rate': 0.3, 'max_depth': 15, 'n_estimators': 200}
T2、TimeSeriesSplit=GSCV模型调参
输出XGBR_GSCV模型最佳得分、最优参数：0.8772,{'learning_rate': 0.15, 'max_depth': 3, 'n_estimators': 200}
XGBR_TimeS_GSCV time： 365.73213645175
XGBoost Score value: 0.8392863414585984
XGBoost R2 value: 0.8392863414585984
XGBoost MAE value: 2.265871170374352
XGBoost RMSE value: 3.5301480357113575
1. Fitting 6 folds for each of 320 candidates, totalling 1920 fits 2. [Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers. 3. [Parallel(n_jobs=1)]: Done 1920 out of 1920 | elapsed: 6.1min finished 4. 0.601753 (0.041626) with: {'learning_rate': 0.03, 'max_depth': 1, 'n_estimators': 50} 5. 0.741963 (0.052567) with: {'learning_rate': 0.03, 'max_depth': 1, 'n_estimators': 100} 6. 0.769275 (0.057973) with: {'learning_rate': 0.03, 'max_depth': 1, 'n_estimators': 150} 7. 0.777850 (0.062691) with: {'learning_rate': 0.03, 'max_depth': 1, 'n_estimators': 200} 8. 0.761917 (0.044601) with: {'learning_rate': 0.03, 'max_depth': 3, 'n_estimators': 50} 9. 0.849871 (0.032589) with: {'learning_rate': 0.03, 'max_depth': 3, 'n_estimators': 100} 10. 0.860943 (0.036123) with: {'learning_rate': 0.03, 'max_depth': 3, 'n_estimators': 150} 11. 0.865884 (0.036296) with: {'learning_rate': 0.03, 'max_depth': 3, 'n_estimators': 200} 12. 0.768191 (0.046584) with: {'learning_rate': 0.03, 'max_depth': 5, 'n_estimators': 50} 13. 0.847475 (0.037179) with: {'learning_rate': 0.03, 'max_depth': 5, 'n_estimators': 100} 14. 0.857618 (0.034498) with: {'learning_rate': 0.03, 'max_depth': 5, 'n_estimators': 150} 15. 0.860371 (0.034667) with: {'learning_rate': 0.03, 'max_depth': 5, 'n_estimators': 200} 16. 0.762532 (0.043118) with: {'learning_rate': 0.03, 'max_depth': 7, 'n_estimators': 50} 17. 0.838141 (0.032139) with: {'learning_rate': 0.03, 'max_depth': 7, 'n_estimators': 100} 18. 0.846885 (0.027194) with: {'learning_rate': 0.03, 'max_depth': 7, 'n_estimators': 150} 19. 0.850041 (0.025481) with: {'learning_rate': 0.03, 'max_depth': 7, 'n_estimators': 200} 20. 0.757383 (0.050920) with: {'learning_rate': 0.03, 'max_depth': 9, 'n_estimators': 50} 21. 0.834539 (0.037476) with: {'learning_rate': 0.03, 'max_depth': 9, 'n_estimators': 100} 22. 0.845794 (0.033418) with: {'learning_rate': 0.03, 'max_depth': 9, 'n_estimators': 150} 23. 0.848075 (0.032044) with: {'learning_rate': 0.03, 'max_depth': 9, 'n_estimators': 200} 24. 0.754782 (0.053572) with: {'learning_rate': 0.03, 'max_depth': 11, 'n_estimators': 50} 25. 0.831093 (0.039371) with: {'learning_rate': 0.03, 'max_depth': 11, 'n_estimators': 100} 26. 0.838982 (0.034142) with: {'learning_rate': 0.03, 'max_depth': 11, 'n_estimators': 150} 27. 0.841296 (0.031967) with: {'learning_rate': 0.03, 'max_depth': 11, 'n_estimators': 200} 28. 0.756791 (0.051747) with: {'learning_rate': 0.03, 'max_depth': 13, 'n_estimators': 50} 29. 0.830920 (0.039090) with: {'learning_rate': 0.03, 'max_depth': 13, 'n_estimators': 100} 30. 0.840551 (0.032427) with: {'learning_rate': 0.03, 'max_depth': 13, 'n_estimators': 150} 31. 0.843931 (0.030071) with: {'learning_rate': 0.03, 'max_depth': 13, 'n_estimators': 200} 32. 0.756117 (0.054046) with: {'learning_rate': 0.03, 'max_depth': 15, 'n_estimators': 50} 33. 0.831666 (0.040286) with: {'learning_rate': 0.03, 'max_depth': 15, 'n_estimators': 100} 34. 0.840035 (0.034584) with: {'learning_rate': 0.03, 'max_depth': 15, 'n_estimators': 150} 35. 0.843151 (0.032286) with: {'learning_rate': 0.03, 'max_depth': 15, 'n_estimators': 200} 36. 0.745626 (0.052724) with: {'learning_rate': 0.06, 'max_depth': 1, 'n_estimators': 50} 37. 0.777825 (0.062635) with: {'learning_rate': 0.06, 'max_depth': 1, 'n_estimators': 100} 38. 0.790555 (0.063551) with: {'learning_rate': 0.06, 'max_depth': 1, 'n_estimators': 150} 39. 0.795161 (0.067328) with: {'learning_rate': 0.06, 'max_depth': 1, 'n_estimators': 200} 40. 0.850889 (0.032347) with: {'learning_rate': 0.06, 'max_depth': 3, 'n_estimators': 50} 41. 0.867786 (0.034764) with: {'learning_rate': 0.06, 'max_depth': 3, 'n_estimators': 100} 42. 0.870313 (0.035557) with: {'learning_rate': 0.06, 'max_depth': 3, 'n_estimators': 150} 43. 0.870957 (0.036189) with: {'learning_rate': 0.06, 'max_depth': 3, 'n_estimators': 200} 44. 0.850339 (0.038543) with: {'learning_rate': 0.06, 'max_depth': 5, 'n_estimators': 50} 45. 0.864939 (0.034315) with: {'learning_rate': 0.06, 'max_depth': 5, 'n_estimators': 100} 46. 0.865762 (0.033280) with: {'learning_rate': 0.06, 'max_depth': 5, 'n_estimators': 150} 47. 0.865658 (0.032928) with: {'learning_rate': 0.06, 'max_depth': 5, 'n_estimators': 200} 48. 0.839195 (0.034252) with: {'learning_rate': 0.06, 'max_depth': 7, 'n_estimators': 50} 49. 0.852720 (0.027235) with: {'learning_rate': 0.06, 'max_depth': 7, 'n_estimators': 100} 50. 0.853702 (0.027123) with: {'learning_rate': 0.06, 'max_depth': 7, 'n_estimators': 150} 51. 0.853363 (0.026771) with: {'learning_rate': 0.06, 'max_depth': 7, 'n_estimators': 200} 52. 0.835426 (0.038498) with: {'learning_rate': 0.06, 'max_depth': 9, 'n_estimators': 50} 53. 0.850673 (0.029506) with: {'learning_rate': 0.06, 'max_depth': 9, 'n_estimators': 100} 54. 0.851901 (0.028517) with: {'learning_rate': 0.06, 'max_depth': 9, 'n_estimators': 150} 55. 0.852140 (0.028341) with: {'learning_rate': 0.06, 'max_depth': 9, 'n_estimators': 200} 56. 0.830953 (0.038574) with: {'learning_rate': 0.06, 'max_depth': 11, 'n_estimators': 50} 57. 0.843297 (0.032231) with: {'learning_rate': 0.06, 'max_depth': 11, 'n_estimators': 100} 58. 0.844927 (0.031055) with: {'learning_rate': 0.06, 'max_depth': 11, 'n_estimators': 150} 59. 0.845079 (0.030915) with: {'learning_rate': 0.06, 'max_depth': 11, 'n_estimators': 200} 60. 0.832709 (0.036911) with: {'learning_rate': 0.06, 'max_depth': 13, 'n_estimators': 50} 61. 0.844690 (0.029680) with: {'learning_rate': 0.06, 'max_depth': 13, 'n_estimators': 100} 62. 0.846225 (0.028501) with: {'learning_rate': 0.06, 'max_depth': 13, 'n_estimators': 150} 63. 0.846421 (0.028346) with: {'learning_rate': 0.06, 'max_depth': 13, 'n_estimators': 200} 64. 0.832991 (0.037219) with: {'learning_rate': 0.06, 'max_depth': 15, 'n_estimators': 50} 65. 0.846270 (0.027385) with: {'learning_rate': 0.06, 'max_depth': 15, 'n_estimators': 100} 66. 0.847907 (0.026163) with: {'learning_rate': 0.06, 'max_depth': 15, 'n_estimators': 150} 67. 0.848179 (0.025976) with: {'learning_rate': 0.06, 'max_depth': 15, 'n_estimators': 200} 68. 0.769494 (0.058840) with: {'learning_rate': 0.09, 'max_depth': 1, 'n_estimators': 50} 69. 0.791904 (0.061566) with: {'learning_rate': 0.09, 'max_depth': 1, 'n_estimators': 100} 70. 0.798994 (0.066574) with: {'learning_rate': 0.09, 'max_depth': 1, 'n_estimators': 150} 71. 0.803098 (0.068958) with: {'learning_rate': 0.09, 'max_depth': 1, 'n_estimators': 200} 72. 0.857212 (0.039482) with: {'learning_rate': 0.09, 'max_depth': 3, 'n_estimators': 50} 73. 0.864690 (0.041052) with: {'learning_rate': 0.09, 'max_depth': 3, 'n_estimators': 100} 74. 0.866892 (0.042026) with: {'learning_rate': 0.09, 'max_depth': 3, 'n_estimators': 150} 75. 0.867056 (0.044514) with: {'learning_rate': 0.09, 'max_depth': 3, 'n_estimators': 200} 76. 0.863862 (0.033670) with: {'learning_rate': 0.09, 'max_depth': 5, 'n_estimators': 50} 77. 0.867507 (0.032224) with: {'learning_rate': 0.09, 'max_depth': 5, 'n_estimators': 100} 78. 0.867579 (0.032191) with: {'learning_rate': 0.09, 'max_depth': 5, 'n_estimators': 150} 79. 0.867328 (0.032260) with: {'learning_rate': 0.09, 'max_depth': 5, 'n_estimators': 200} 80. 0.847872 (0.030395) with: {'learning_rate': 0.09, 'max_depth': 7, 'n_estimators': 50} 81. 0.851244 (0.028736) with: {'learning_rate': 0.09, 'max_depth': 7, 'n_estimators': 100} 82. 0.851237 (0.028451) with: {'learning_rate': 0.09, 'max_depth': 7, 'n_estimators': 150} 83. 0.851150 (0.028505) with: {'learning_rate': 0.09, 'max_depth': 7, 'n_estimators': 200} 84. 0.852037 (0.030096) with: {'learning_rate': 0.09, 'max_depth': 9, 'n_estimators': 50} 85. 0.856354 (0.027161) with: {'learning_rate': 0.09, 'max_depth': 9, 'n_estimators': 100} 86. 0.856581 (0.027075) with: {'learning_rate': 0.09, 'max_depth': 9, 'n_estimators': 150} 87. 0.856585 (0.027095) with: {'learning_rate': 0.09, 'max_depth': 9, 'n_estimators': 200} 88. 0.842612 (0.037117) with: {'learning_rate': 0.09, 'max_depth': 11, 'n_estimators': 50} 89. 0.846502 (0.034153) with: {'learning_rate': 0.09, 'max_depth': 11, 'n_estimators': 100} 90. 0.846631 (0.034112) with: {'learning_rate': 0.09, 'max_depth': 11, 'n_estimators': 150} 91. 0.846628 (0.034114) with: {'learning_rate': 0.09, 'max_depth': 11, 'n_estimators': 200} 92. 0.837185 (0.045250) with: {'learning_rate': 0.09, 'max_depth': 13, 'n_estimators': 50} 93. 0.841045 (0.042592) with: {'learning_rate': 0.09, 'max_depth': 13, 'n_estimators': 100} 94. 0.841290 (0.042421) with: {'learning_rate': 0.09, 'max_depth': 13, 'n_estimators': 150} 95. 0.841292 (0.042423) with: {'learning_rate': 0.09, 'max_depth': 13, 'n_estimators': 200} 96. 0.836856 (0.044501) with: {'learning_rate': 0.09, 'max_depth': 15, 'n_estimators': 50} 97. 0.841215 (0.041712) with: {'learning_rate': 0.09, 'max_depth': 15, 'n_estimators': 100} 98. 0.841468 (0.041614) with: {'learning_rate': 0.09, 'max_depth': 15, 'n_estimators': 150} 99. 0.841467 (0.041616) with: {'learning_rate': 0.09, 'max_depth': 15, 'n_estimators': 200} 100. 0.780448 (0.061299) with: {'learning_rate': 0.12, 'max_depth': 1, 'n_estimators': 50} 101. 0.795945 (0.066888) with: {'learning_rate': 0.12, 'max_depth': 1, 'n_estimators': 100} 102. 0.802161 (0.068522) with: {'learning_rate': 0.12, 'max_depth': 1, 'n_estimators': 150} 103. 0.802621 (0.068183) with: {'learning_rate': 0.12, 'max_depth': 1, 'n_estimators': 200} 104. 0.865637 (0.033886) with: {'learning_rate': 0.12, 'max_depth': 3, 'n_estimators': 50} 105. 0.867696 (0.038014) with: {'learning_rate': 0.12, 'max_depth': 3, 'n_estimators': 100} 106. 0.867815 (0.038860) with: {'learning_rate': 0.12, 'max_depth': 3, 'n_estimators': 150} 107. 0.867725 (0.040073) with: {'learning_rate': 0.12, 'max_depth': 3, 'n_estimators': 200} 108. 0.862285 (0.036140) with: {'learning_rate': 0.12, 'max_depth': 5, 'n_estimators': 50} 109. 0.862022 (0.035454) with: {'learning_rate': 0.12, 'max_depth': 5, 'n_estimators': 100} 110. 0.860983 (0.034947) with: {'learning_rate': 0.12, 'max_depth': 5, 'n_estimators': 150} 111. 0.860190 (0.035108) with: {'learning_rate': 0.12, 'max_depth': 5, 'n_estimators': 200} 112. 0.842677 (0.036587) with: {'learning_rate': 0.12, 'max_depth': 7, 'n_estimators': 50} 113. 0.843950 (0.035671) with: {'learning_rate': 0.12, 'max_depth': 7, 'n_estimators': 100} 114. 0.843875 (0.035644) with: {'learning_rate': 0.12, 'max_depth': 7, 'n_estimators': 150} 115. 0.843844 (0.035605) with: {'learning_rate': 0.12, 'max_depth': 7, 'n_estimators': 200} 116. 0.843541 (0.033950) with: {'learning_rate': 0.12, 'max_depth': 9, 'n_estimators': 50} 117. 0.845166 (0.033044) with: {'learning_rate': 0.12, 'max_depth': 9, 'n_estimators': 100} 118. 0.845168 (0.033025) with: {'learning_rate': 0.12, 'max_depth': 9, 'n_estimators': 150} 119. 0.845168 (0.033025) with: {'learning_rate': 0.12, 'max_depth': 9, 'n_estimators': 200} 120. 0.836159 (0.037345) with: {'learning_rate': 0.12, 'max_depth': 11, 'n_estimators': 50} 121. 0.838014 (0.036395) with: {'learning_rate': 0.12, 'max_depth': 11, 'n_estimators': 100} 122. 0.838049 (0.036371) with: {'learning_rate': 0.12, 'max_depth': 11, 'n_estimators': 150} 123. 0.838049 (0.036371) with: {'learning_rate': 0.12, 'max_depth': 11, 'n_estimators': 200} 124. 0.836390 (0.036978) with: {'learning_rate': 0.12, 'max_depth': 13, 'n_estimators': 50} 125. 0.838276 (0.035834) with: {'learning_rate': 0.12, 'max_depth': 13, 'n_estimators': 100} 126. 0.838287 (0.035842) with: {'learning_rate': 0.12, 'max_depth': 13, 'n_estimators': 150} 127. 0.838287 (0.035842) with: {'learning_rate': 0.12, 'max_depth': 13, 'n_estimators': 200} 128. 0.832744 (0.040432) with: {'learning_rate': 0.12, 'max_depth': 15, 'n_estimators': 50} 129. 0.834029 (0.039399) with: {'learning_rate': 0.12, 'max_depth': 15, 'n_estimators': 100} 130. 0.834041 (0.039407) with: {'learning_rate': 0.12, 'max_depth': 15, 'n_estimators': 150} 131. 0.834041 (0.039407) with: {'learning_rate': 0.12, 'max_depth': 15, 'n_estimators': 200} 132. 0.788286 (0.060777) with: {'learning_rate': 0.15, 'max_depth': 1, 'n_estimators': 50} 133. 0.800992 (0.066420) with: {'learning_rate': 0.15, 'max_depth': 1, 'n_estimators': 100} 134. 0.805570 (0.064051) with: {'learning_rate': 0.15, 'max_depth': 1, 'n_estimators': 150} 135. 0.804252 (0.066082) with: {'learning_rate': 0.15, 'max_depth': 1, 'n_estimators': 200} 136. 0.873263 (0.037228) with: {'learning_rate': 0.15, 'max_depth': 3, 'n_estimators': 50} 137. 0.876110 (0.038150) with: {'learning_rate': 0.15, 'max_depth': 3, 'n_estimators': 100} 138. 0.876937 (0.036679) with: {'learning_rate': 0.15, 'max_depth': 3, 'n_estimators': 150} 139. 0.877158 (0.036059) with: {'learning_rate': 0.15, 'max_depth': 3, 'n_estimators': 200} 140. 0.866913 (0.033984) with: {'learning_rate': 0.15, 'max_depth': 5, 'n_estimators': 50} 141. 0.865987 (0.034375) with: {'learning_rate': 0.15, 'max_depth': 5, 'n_estimators': 100} 142. 0.865887 (0.034338) with: {'learning_rate': 0.15, 'max_depth': 5, 'n_estimators': 150} 143. 0.865612 (0.034281) with: {'learning_rate': 0.15, 'max_depth': 5, 'n_estimators': 200} 144. 0.855167 (0.023013) with: {'learning_rate': 0.15, 'max_depth': 7, 'n_estimators': 50} 145. 0.854927 (0.022918) with: {'learning_rate': 0.15, 'max_depth': 7, 'n_estimators': 100} 146. 0.854869 (0.022988) with: {'learning_rate': 0.15, 'max_depth': 7, 'n_estimators': 150} 147. 0.854869 (0.022989) with: {'learning_rate': 0.15, 'max_depth': 7, 'n_estimators': 200} 148. 0.844406 (0.031283) with: {'learning_rate': 0.15, 'max_depth': 9, 'n_estimators': 50} 149. 0.844863 (0.031062) with: {'learning_rate': 0.15, 'max_depth': 9, 'n_estimators': 100} 150. 0.844860 (0.031057) with: {'learning_rate': 0.15, 'max_depth': 9, 'n_estimators': 150} 151. 0.844860 (0.031057) with: {'learning_rate': 0.15, 'max_depth': 9, 'n_estimators': 200} 152. 0.841634 (0.027276) with: {'learning_rate': 0.15, 'max_depth': 11, 'n_estimators': 50} 153. 0.842250 (0.027120) with: {'learning_rate': 0.15, 'max_depth': 11, 'n_estimators': 100} 154. 0.842250 (0.027120) with: {'learning_rate': 0.15, 'max_depth': 11, 'n_estimators': 150} 155. 0.842250 (0.027120) with: {'learning_rate': 0.15, 'max_depth': 11, 'n_estimators': 200} 156. 0.831977 (0.045021) with: {'learning_rate': 0.15, 'max_depth': 13, 'n_estimators': 50} 157. 0.832695 (0.044631) with: {'learning_rate': 0.15, 'max_depth': 13, 'n_estimators': 100} 158. 0.832695 (0.044631) with: {'learning_rate': 0.15, 'max_depth': 13, 'n_estimators': 150} 159. 0.832695 (0.044631) with: {'learning_rate': 0.15, 'max_depth': 13, 'n_estimators': 200} 160. 0.834018 (0.038130) with: {'learning_rate': 0.15, 'max_depth': 15, 'n_estimators': 50} 161. 0.834701 (0.037810) with: {'learning_rate': 0.15, 'max_depth': 15, 'n_estimators': 100} 162. 0.834701 (0.037809) with: {'learning_rate': 0.15, 'max_depth': 15, 'n_estimators': 150} 163. 0.834701 (0.037809) with: {'learning_rate': 0.15, 'max_depth': 15, 'n_estimators': 200} 164. 0.792071 (0.063119) with: {'learning_rate': 0.18, 'max_depth': 1, 'n_estimators': 50} 165. 0.799122 (0.071840) with: {'learning_rate': 0.18, 'max_depth': 1, 'n_estimators': 100} 166. 0.799956 (0.073676) with: {'learning_rate': 0.18, 'max_depth': 1, 'n_estimators': 150} 167. 0.800800 (0.072044) with: {'learning_rate': 0.18, 'max_depth': 1, 'n_estimators': 200} 168. 0.862375 (0.033146) with: {'learning_rate': 0.18, 'max_depth': 3, 'n_estimators': 50} 169. 0.861233 (0.039972) with: {'learning_rate': 0.18, 'max_depth': 3, 'n_estimators': 100} 170. 0.859582 (0.042319) with: {'learning_rate': 0.18, 'max_depth': 3, 'n_estimators': 150} 171. 0.859903 (0.042120) with: {'learning_rate': 0.18, 'max_depth': 3, 'n_estimators': 200} 172. 0.860906 (0.038278) with: {'learning_rate': 0.18, 'max_depth': 5, 'n_estimators': 50} 173. 0.860003 (0.039017) with: {'learning_rate': 0.18, 'max_depth': 5, 'n_estimators': 100} 174. 0.859676 (0.039497) with: {'learning_rate': 0.18, 'max_depth': 5, 'n_estimators': 150} 175. 0.859539 (0.039609) with: {'learning_rate': 0.18, 'max_depth': 5, 'n_estimators': 200} 176. 0.859172 (0.030006) with: {'learning_rate': 0.18, 'max_depth': 7, 'n_estimators': 50} 177. 0.859255 (0.030341) with: {'learning_rate': 0.18, 'max_depth': 7, 'n_estimators': 100} 178. 0.859227 (0.030337) with: {'learning_rate': 0.18, 'max_depth': 7, 'n_estimators': 150} 179. 0.859227 (0.030337) with: {'learning_rate': 0.18, 'max_depth': 7, 'n_estimators': 200} 180. 0.846028 (0.030136) with: {'learning_rate': 0.18, 'max_depth': 9, 'n_estimators': 50} 181. 0.846116 (0.030054) with: {'learning_rate': 0.18, 'max_depth': 9, 'n_estimators': 100} 182. 0.846116 (0.030054) with: {'learning_rate': 0.18, 'max_depth': 9, 'n_estimators': 150} 183. 0.846116 (0.030054) with: {'learning_rate': 0.18, 'max_depth': 9, 'n_estimators': 200} 184. 0.835031 (0.045618) with: {'learning_rate': 0.18, 'max_depth': 11, 'n_estimators': 50} 185. 0.835256 (0.045504) with: {'learning_rate': 0.18, 'max_depth': 11, 'n_estimators': 100} 186. 0.835256 (0.045504) with: {'learning_rate': 0.18, 'max_depth': 11, 'n_estimators': 150} 187. 0.835256 (0.045504) with: {'learning_rate': 0.18, 'max_depth': 11, 'n_estimators': 200} 188. 0.839579 (0.037195) with: {'learning_rate': 0.18, 'max_depth': 13, 'n_estimators': 50} 189. 0.839839 (0.036966) with: {'learning_rate': 0.18, 'max_depth': 13, 'n_estimators': 100} 190. 0.839839 (0.036966) with: {'learning_rate': 0.18, 'max_depth': 13, 'n_estimators': 150} 191. 0.839839 (0.036966) with: {'learning_rate': 0.18, 'max_depth': 13, 'n_estimators': 200} 192. 0.834138 (0.042687) with: {'learning_rate': 0.18, 'max_depth': 15, 'n_estimators': 50} 193. 0.834406 (0.042569) with: {'learning_rate': 0.18, 'max_depth': 15, 'n_estimators': 100} 194. 0.834406 (0.042569) with: {'learning_rate': 0.18, 'max_depth': 15, 'n_estimators': 150} 195. 0.834406 (0.042569) with: {'learning_rate': 0.18, 'max_depth': 15, 'n_estimators': 200} 196. 0.791549 (0.066137) with: {'learning_rate': 0.21, 'max_depth': 1, 'n_estimators': 50} 197. 0.799056 (0.069836) with: {'learning_rate': 0.21, 'max_depth': 1, 'n_estimators': 100} 198. 0.799127 (0.072385) with: {'learning_rate': 0.21, 'max_depth': 1, 'n_estimators': 150} 199. 0.798508 (0.071937) with: {'learning_rate': 0.21, 'max_depth': 1, 'n_estimators': 200} 200. 0.872043 (0.033671) with: {'learning_rate': 0.21, 'max_depth': 3, 'n_estimators': 50} 201. 0.874572 (0.031613) with: {'learning_rate': 0.21, 'max_depth': 3, 'n_estimators': 100} 202. 0.873857 (0.031410) with: {'learning_rate': 0.21, 'max_depth': 3, 'n_estimators': 150} 203. 0.873438 (0.029881) with: {'learning_rate': 0.21, 'max_depth': 3, 'n_estimators': 200} 204. 0.860836 (0.038659) with: {'learning_rate': 0.21, 'max_depth': 5, 'n_estimators': 50} 205. 0.859716 (0.038468) with: {'learning_rate': 0.21, 'max_depth': 5, 'n_estimators': 100} 206. 0.859700 (0.038961) with: {'learning_rate': 0.21, 'max_depth': 5, 'n_estimators': 150} 207. 0.859774 (0.039022) with: {'learning_rate': 0.21, 'max_depth': 5, 'n_estimators': 200} 208. 0.850274 (0.038069) with: {'learning_rate': 0.21, 'max_depth': 7, 'n_estimators': 50} 209. 0.850067 (0.038088) with: {'learning_rate': 0.21, 'max_depth': 7, 'n_estimators': 100} 210. 0.850058 (0.038076) with: {'learning_rate': 0.21, 'max_depth': 7, 'n_estimators': 150} 211. 0.850058 (0.038076) with: {'learning_rate': 0.21, 'max_depth': 7, 'n_estimators': 200} 212. 0.836878 (0.047811) with: {'learning_rate': 0.21, 'max_depth': 9, 'n_estimators': 50} 213. 0.836854 (0.047828) with: {'learning_rate': 0.21, 'max_depth': 9, 'n_estimators': 100} 214. 0.836854 (0.047828) with: {'learning_rate': 0.21, 'max_depth': 9, 'n_estimators': 150} 215. 0.836854 (0.047828) with: {'learning_rate': 0.21, 'max_depth': 9, 'n_estimators': 200} 216. 0.832230 (0.054081) with: {'learning_rate': 0.21, 'max_depth': 11, 'n_estimators': 50} 217. 0.832294 (0.054084) with: {'learning_rate': 0.21, 'max_depth': 11, 'n_estimators': 100} 218. 0.832294 (0.054084) with: {'learning_rate': 0.21, 'max_depth': 11, 'n_estimators': 150} 219. 0.832294 (0.054084) with: {'learning_rate': 0.21, 'max_depth': 11, 'n_estimators': 200} 220. 0.828600 (0.053761) with: {'learning_rate': 0.21, 'max_depth': 13, 'n_estimators': 50} 221. 0.828676 (0.053745) with: {'learning_rate': 0.21, 'max_depth': 13, 'n_estimators': 100} 222. 0.828676 (0.053745) with: {'learning_rate': 0.21, 'max_depth': 13, 'n_estimators': 150} 223. 0.828676 (0.053745) with: {'learning_rate': 0.21, 'max_depth': 13, 'n_estimators': 200} 224. 0.835965 (0.043150) with: {'learning_rate': 0.21, 'max_depth': 15, 'n_estimators': 50} 225. 0.836031 (0.043121) with: {'learning_rate': 0.21, 'max_depth': 15, 'n_estimators': 100} 226. 0.836031 (0.043121) with: {'learning_rate': 0.21, 'max_depth': 15, 'n_estimators': 150} 227. 0.836031 (0.043121) with: {'learning_rate': 0.21, 'max_depth': 15, 'n_estimators': 200} 228. 0.795481 (0.067871) with: {'learning_rate': 0.24, 'max_depth': 1, 'n_estimators': 50} 229. 0.801605 (0.071016) with: {'learning_rate': 0.24, 'max_depth': 1, 'n_estimators': 100} 230. 0.800496 (0.071460) with: {'learning_rate': 0.24, 'max_depth': 1, 'n_estimators': 150} 231. 0.797624 (0.071779) with: {'learning_rate': 0.24, 'max_depth': 1, 'n_estimators': 200} 232. 0.874398 (0.045566) with: {'learning_rate': 0.24, 'max_depth': 3, 'n_estimators': 50} 233. 0.874511 (0.044248) with: {'learning_rate': 0.24, 'max_depth': 3, 'n_estimators': 100} 234. 0.872990 (0.044873) with: {'learning_rate': 0.24, 'max_depth': 3, 'n_estimators': 150} 235. 0.872426 (0.045030) with: {'learning_rate': 0.24, 'max_depth': 3, 'n_estimators': 200} 236. 0.864891 (0.035698) with: {'learning_rate': 0.24, 'max_depth': 5, 'n_estimators': 50} 237. 0.864877 (0.036296) with: {'learning_rate': 0.24, 'max_depth': 5, 'n_estimators': 100} 238. 0.864924 (0.036331) with: {'learning_rate': 0.24, 'max_depth': 5, 'n_estimators': 150} 239. 0.864914 (0.036352) with: {'learning_rate': 0.24, 'max_depth': 5, 'n_estimators': 200} 240. 0.842421 (0.037213) with: {'learning_rate': 0.24, 'max_depth': 7, 'n_estimators': 50} 241. 0.842429 (0.037197) with: {'learning_rate': 0.24, 'max_depth': 7, 'n_estimators': 100} 242. 0.842429 (0.037197) with: {'learning_rate': 0.24, 'max_depth': 7, 'n_estimators': 150} 243. 0.842429 (0.037197) with: {'learning_rate': 0.24, 'max_depth': 7, 'n_estimators': 200} 244. 0.837901 (0.040525) with: {'learning_rate': 0.24, 'max_depth': 9, 'n_estimators': 50} 245. 0.837940 (0.040483) with: {'learning_rate': 0.24, 'max_depth': 9, 'n_estimators': 100} 246. 0.837940 (0.040483) with: {'learning_rate': 0.24, 'max_depth': 9, 'n_estimators': 150} 247. 0.837940 (0.040483) with: {'learning_rate': 0.24, 'max_depth': 9, 'n_estimators': 200} 248. 0.840851 (0.034598) with: {'learning_rate': 0.24, 'max_depth': 11, 'n_estimators': 50} 249. 0.840865 (0.034607) with: {'learning_rate': 0.24, 'max_depth': 11, 'n_estimators': 100} 250. 0.840865 (0.034607) with: {'learning_rate': 0.24, 'max_depth': 11, 'n_estimators': 150} 251. 0.840865 (0.034607) with: {'learning_rate': 0.24, 'max_depth': 11, 'n_estimators': 200} 252. 0.836298 (0.042239) with: {'learning_rate': 0.24, 'max_depth': 13, 'n_estimators': 50} 253. 0.836310 (0.042240) with: {'learning_rate': 0.24, 'max_depth': 13, 'n_estimators': 100} 254. 0.836310 (0.042240) with: {'learning_rate': 0.24, 'max_depth': 13, 'n_estimators': 150} 255. 0.836310 (0.042240) with: {'learning_rate': 0.24, 'max_depth': 13, 'n_estimators': 200} 256. 0.839400 (0.036339) with: {'learning_rate': 0.24, 'max_depth': 15, 'n_estimators': 50} 257. 0.839409 (0.036336) with: {'learning_rate': 0.24, 'max_depth': 15, 'n_estimators': 100} 258. 0.839409 (0.036336) with: {'learning_rate': 0.24, 'max_depth': 15, 'n_estimators': 150} 259. 0.839409 (0.036336) with: {'learning_rate': 0.24, 'max_depth': 15, 'n_estimators': 200} 260. 0.800111 (0.064232) with: {'learning_rate': 0.27, 'max_depth': 1, 'n_estimators': 50} 261. 0.802720 (0.064531) with: {'learning_rate': 0.27, 'max_depth': 1, 'n_estimators': 100} 262. 0.801777 (0.063193) with: {'learning_rate': 0.27, 'max_depth': 1, 'n_estimators': 150} 263. 0.800700 (0.063971) with: {'learning_rate': 0.27, 'max_depth': 1, 'n_estimators': 200} 264. 0.861053 (0.043753) with: {'learning_rate': 0.27, 'max_depth': 3, 'n_estimators': 50} 265. 0.864884 (0.043096) with: {'learning_rate': 0.27, 'max_depth': 3, 'n_estimators': 100} 266. 0.864313 (0.043066) with: {'learning_rate': 0.27, 'max_depth': 3, 'n_estimators': 150} 267. 0.864089 (0.043224) with: {'learning_rate': 0.27, 'max_depth': 3, 'n_estimators': 200} 268. 0.858039 (0.040074) with: {'learning_rate': 0.27, 'max_depth': 5, 'n_estimators': 50} 269. 0.857603 (0.039677) with: {'learning_rate': 0.27, 'max_depth': 5, 'n_estimators': 100} 270. 0.857465 (0.039709) with: {'learning_rate': 0.27, 'max_depth': 5, 'n_estimators': 150} 271. 0.857458 (0.039712) with: {'learning_rate': 0.27, 'max_depth': 5, 'n_estimators': 200} 272. 0.850983 (0.028739) with: {'learning_rate': 0.27, 'max_depth': 7, 'n_estimators': 50} 273. 0.850913 (0.029035) with: {'learning_rate': 0.27, 'max_depth': 7, 'n_estimators': 100} 274. 0.850913 (0.029035) with: {'learning_rate': 0.27, 'max_depth': 7, 'n_estimators': 150} 275. 0.850913 (0.029035) with: {'learning_rate': 0.27, 'max_depth': 7, 'n_estimators': 200} 276. 0.838340 (0.046207) with: {'learning_rate': 0.27, 'max_depth': 9, 'n_estimators': 50} 277. 0.838347 (0.046212) with: {'learning_rate': 0.27, 'max_depth': 9, 'n_estimators': 100} 278. 0.838347 (0.046212) with: {'learning_rate': 0.27, 'max_depth': 9, 'n_estimators': 150} 279. 0.838347 (0.046212) with: {'learning_rate': 0.27, 'max_depth': 9, 'n_estimators': 200} 280. 0.839129 (0.042315) with: {'learning_rate': 0.27, 'max_depth': 11, 'n_estimators': 50} 281. 0.839128 (0.042315) with: {'learning_rate': 0.27, 'max_depth': 11, 'n_estimators': 100} 282. 0.839128 (0.042315) with: {'learning_rate': 0.27, 'max_depth': 11, 'n_estimators': 150} 283. 0.839128 (0.042315) with: {'learning_rate': 0.27, 'max_depth': 11, 'n_estimators': 200} 284. 0.831859 (0.047889) with: {'learning_rate': 0.27, 'max_depth': 13, 'n_estimators': 50} 285. 0.831858 (0.047888) with: {'learning_rate': 0.27, 'max_depth': 13, 'n_estimators': 100} 286. 0.831858 (0.047888) with: {'learning_rate': 0.27, 'max_depth': 13, 'n_estimators': 150} 287. 0.831858 (0.047888) with: {'learning_rate': 0.27, 'max_depth': 13, 'n_estimators': 200} 288. 0.835551 (0.037876) with: {'learning_rate': 0.27, 'max_depth': 15, 'n_estimators': 50} 289. 0.835550 (0.037876) with: {'learning_rate': 0.27, 'max_depth': 15, 'n_estimators': 100} 290. 0.835550 (0.037876) with: {'learning_rate': 0.27, 'max_depth': 15, 'n_estimators': 150} 291. 0.835550 (0.037876) with: {'learning_rate': 0.27, 'max_depth': 15, 'n_estimators': 200} 292. 0.796646 (0.068806) with: {'learning_rate': 0.3, 'max_depth': 1, 'n_estimators': 50} 293. 0.798677 (0.069044) with: {'learning_rate': 0.3, 'max_depth': 1, 'n_estimators': 100} 294. 0.798088 (0.068661) with: {'learning_rate': 0.3, 'max_depth': 1, 'n_estimators': 150} 295. 0.795781 (0.067476) with: {'learning_rate': 0.3, 'max_depth': 1, 'n_estimators': 200} 296. 0.869378 (0.040670) with: {'learning_rate': 0.3, 'max_depth': 3, 'n_estimators': 50} 297. 0.869182 (0.039476) with: {'learning_rate': 0.3, 'max_depth': 3, 'n_estimators': 100} 298. 0.869342 (0.038240) with: {'learning_rate': 0.3, 'max_depth': 3, 'n_estimators': 150} 299. 0.868400 (0.038308) with: {'learning_rate': 0.3, 'max_depth': 3, 'n_estimators': 200} 300. 0.868980 (0.030734) with: {'learning_rate': 0.3, 'max_depth': 5, 'n_estimators': 50} 301. 0.868601 (0.031693) with: {'learning_rate': 0.3, 'max_depth': 5, 'n_estimators': 100} 302. 0.868620 (0.031606) with: {'learning_rate': 0.3, 'max_depth': 5, 'n_estimators': 150} 303. 0.868620 (0.031606) with: {'learning_rate': 0.3, 'max_depth': 5, 'n_estimators': 200} 304. 0.859642 (0.026923) with: {'learning_rate': 0.3, 'max_depth': 7, 'n_estimators': 50} 305. 0.859655 (0.026917) with: {'learning_rate': 0.3, 'max_depth': 7, 'n_estimators': 100} 306. 0.859655 (0.026917) with: {'learning_rate': 0.3, 'max_depth': 7, 'n_estimators': 150} 307. 0.859655 (0.026917) with: {'learning_rate': 0.3, 'max_depth': 7, 'n_estimators': 200} 308. 0.843922 (0.039863) with: {'learning_rate': 0.3, 'max_depth': 9, 'n_estimators': 50} 309. 0.843921 (0.039864) with: {'learning_rate': 0.3, 'max_depth': 9, 'n_estimators': 100} 310. 0.843921 (0.039864) with: {'learning_rate': 0.3, 'max_depth': 9, 'n_estimators': 150} 311. 0.843921 (0.039864) with: {'learning_rate': 0.3, 'max_depth': 9, 'n_estimators': 200} 312. 0.836648 (0.043075) with: {'learning_rate': 0.3, 'max_depth': 11, 'n_estimators': 50} 313. 0.836648 (0.043075) with: {'learning_rate': 0.3, 'max_depth': 11, 'n_estimators': 100} 314. 0.836648 (0.043075) with: {'learning_rate': 0.3, 'max_depth': 11, 'n_estimators': 150} 315. 0.836648 (0.043075) with: {'learning_rate': 0.3, 'max_depth': 11, 'n_estimators': 200} 316. 0.833262 (0.043352) with: {'learning_rate': 0.3, 'max_depth': 13, 'n_estimators': 50} 317. 0.833262 (0.043352) with: {'learning_rate': 0.3, 'max_depth': 13, 'n_estimators': 100} 318. 0.833262 (0.043352) with: {'learning_rate': 0.3, 'max_depth': 13, 'n_estimators': 150} 319. 0.833262 (0.043352) with: {'learning_rate': 0.3, 'max_depth': 13, 'n_estimators': 200} 320. 0.828890 (0.049491) with: {'learning_rate': 0.3, 'max_depth': 15, 'n_estimators': 50} 321. 0.828890 (0.049491) with: {'learning_rate': 0.3, 'max_depth': 15, 'n_estimators': 100} 322. 0.828890 (0.049491) with: {'learning_rate': 0.3, 'max_depth': 15, 'n_estimators': 150} 323. 0.828890 (0.049491) with: {'learning_rate': 0.3, 'max_depth': 15, 'n_estimators': 200}
