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)

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

0.588111 (0.039989) with: {'learning_rate': 0.03, 'max_depth': 1, 'n_estimators': 50}

0.745248 (0.039715) with: {'learning_rate': 0.03, 'max_depth': 1, 'n_estimators': 100}

0.780673 (0.041418) with: {'learning_rate': 0.03, 'max_depth': 1, 'n_estimators': 150}

0.794564 (0.045098) with: {'learning_rate': 0.03, 'max_depth': 1, 'n_estimators': 200}

0.739650 (0.048542) with: {'learning_rate': 0.03, 'max_depth': 3, 'n_estimators': 50}

0.827152 (0.051752) with: {'learning_rate': 0.03, 'max_depth': 3, 'n_estimators': 100}

0.843543 (0.056119) with: {'learning_rate': 0.03, 'max_depth': 3, 'n_estimators': 150}

0.849557 (0.055848) with: {'learning_rate': 0.03, 'max_depth': 3, 'n_estimators': 200}

0.740037 (0.040934) with: {'learning_rate': 0.03, 'max_depth': 5, 'n_estimators': 50}

0.826966 (0.045216) with: {'learning_rate': 0.03, 'max_depth': 5, 'n_estimators': 100}

0.841845 (0.047665) with: {'learning_rate': 0.03, 'max_depth': 5, 'n_estimators': 150}

0.845978 (0.047794) with: {'learning_rate': 0.03, 'max_depth': 5, 'n_estimators': 200}

0.720503 (0.038676) with: {'learning_rate': 0.03, 'max_depth': 7, 'n_estimators': 50}

0.798275 (0.047791) with: {'learning_rate': 0.03, 'max_depth': 7, 'n_estimators': 100}

0.808659 (0.048699) with: {'learning_rate': 0.03, 'max_depth': 7, 'n_estimators': 150}

0.812894 (0.047902) with: {'learning_rate': 0.03, 'max_depth': 7, 'n_estimators': 200}

0.716254 (0.039716) with: {'learning_rate': 0.03, 'max_depth': 9, 'n_estimators': 50}

0.795603 (0.049370) with: {'learning_rate': 0.03, 'max_depth': 9, 'n_estimators': 100}

0.804215 (0.054399) with: {'learning_rate': 0.03, 'max_depth': 9, 'n_estimators': 150}

0.806022 (0.054965) with: {'learning_rate': 0.03, 'max_depth': 9, 'n_estimators': 200}

0.714920 (0.040201) with: {'learning_rate': 0.03, 'max_depth': 11, 'n_estimators': 50}

0.796940 (0.043692) with: {'learning_rate': 0.03, 'max_depth': 11, 'n_estimators': 100}

0.803563 (0.047487) with: {'learning_rate': 0.03, 'max_depth': 11, 'n_estimators': 150}

0.805639 (0.049146) with: {'learning_rate': 0.03, 'max_depth': 11, 'n_estimators': 200}

0.717114 (0.040552) with: {'learning_rate': 0.03, 'max_depth': 13, 'n_estimators': 50}

0.798669 (0.044140) with: {'learning_rate': 0.03, 'max_depth': 13, 'n_estimators': 100}

0.807001 (0.047485) with: {'learning_rate': 0.03, 'max_depth': 13, 'n_estimators': 150}

0.808231 (0.048622) with: {'learning_rate': 0.03, 'max_depth': 13, 'n_estimators': 200}

0.716787 (0.040747) with: {'learning_rate': 0.03, 'max_depth': 15, 'n_estimators': 50}

0.800528 (0.042525) with: {'learning_rate': 0.03, 'max_depth': 15, 'n_estimators': 100}

0.810075 (0.045364) with: {'learning_rate': 0.03, 'max_depth': 15, 'n_estimators': 150}

0.810928 (0.047001) with: {'learning_rate': 0.03, 'max_depth': 15, 'n_estimators': 200}

0.748057 (0.039107) with: {'learning_rate': 0.06, 'max_depth': 1, 'n_estimators': 50}

0.796450 (0.044658) with: {'learning_rate': 0.06, 'max_depth': 1, 'n_estimators': 100}

0.810749 (0.049107) with: {'learning_rate': 0.06, 'max_depth': 1, 'n_estimators': 150}

0.818271 (0.049566) with: {'learning_rate': 0.06, 'max_depth': 1, 'n_estimators': 200}

0.825470 (0.054236) with: {'learning_rate': 0.06, 'max_depth': 3, 'n_estimators': 50}

0.847820 (0.057729) with: {'learning_rate': 0.06, 'max_depth': 3, 'n_estimators': 100}

0.852501 (0.057970) with: {'learning_rate': 0.06, 'max_depth': 3, 'n_estimators': 150}

0.855974 (0.057133) with: {'learning_rate': 0.06, 'max_depth': 3, 'n_estimators': 200}

0.830130 (0.042166) with: {'learning_rate': 0.06, 'max_depth': 5, 'n_estimators': 50}

0.848818 (0.043202) with: {'learning_rate': 0.06, 'max_depth': 5, 'n_estimators': 100}

0.850634 (0.043955) with: {'learning_rate': 0.06, 'max_depth': 5, 'n_estimators': 150}

0.850776 (0.044242) with: {'learning_rate': 0.06, 'max_depth': 5, 'n_estimators': 200}

0.797091 (0.049104) with: {'learning_rate': 0.06, 'max_depth': 7, 'n_estimators': 50}

0.811453 (0.050410) with: {'learning_rate': 0.06, 'max_depth': 7, 'n_estimators': 100}

0.812925 (0.050391) with: {'learning_rate': 0.06, 'max_depth': 7, 'n_estimators': 150}

0.813141 (0.050317) with: {'learning_rate': 0.06, 'max_depth': 7, 'n_estimators': 200}

0.798523 (0.048830) with: {'learning_rate': 0.06, 'max_depth': 9, 'n_estimators': 50}

0.807724 (0.053522) with: {'learning_rate': 0.06, 'max_depth': 9, 'n_estimators': 100}

0.808858 (0.053694) with: {'learning_rate': 0.06, 'max_depth': 9, 'n_estimators': 150}

0.809064 (0.053787) with: {'learning_rate': 0.06, 'max_depth': 9, 'n_estimators': 200}

0.795488 (0.045973) with: {'learning_rate': 0.06, 'max_depth': 11, 'n_estimators': 50}

0.803783 (0.051639) with: {'learning_rate': 0.06, 'max_depth': 11, 'n_estimators': 100}

0.805366 (0.052070) with: {'learning_rate': 0.06, 'max_depth': 11, 'n_estimators': 150}

0.805499 (0.052113) with: {'learning_rate': 0.06, 'max_depth': 11, 'n_estimators': 200}

0.796173 (0.046698) with: {'learning_rate': 0.06, 'max_depth': 13, 'n_estimators': 50}

0.806388 (0.050425) with: {'learning_rate': 0.06, 'max_depth': 13, 'n_estimators': 100}

0.807511 (0.050917) with: {'learning_rate': 0.06, 'max_depth': 13, 'n_estimators': 150}

0.807696 (0.050925) with: {'learning_rate': 0.06, 'max_depth': 13, 'n_estimators': 200}

0.795853 (0.045518) with: {'learning_rate': 0.06, 'max_depth': 15, 'n_estimators': 50}

0.805835 (0.048817) with: {'learning_rate': 0.06, 'max_depth': 15, 'n_estimators': 100}

0.806752 (0.049863) with: {'learning_rate': 0.06, 'max_depth': 15, 'n_estimators': 150}

0.806967 (0.049886) with: {'learning_rate': 0.06, 'max_depth': 15, 'n_estimators': 200}

0.782405 (0.041673) with: {'learning_rate': 0.09, 'max_depth': 1, 'n_estimators': 50}

0.810724 (0.050393) with: {'learning_rate': 0.09, 'max_depth': 1, 'n_estimators': 100}

0.820115 (0.051026) with: {'learning_rate': 0.09, 'max_depth': 1, 'n_estimators': 150}

0.825857 (0.051649) with: {'learning_rate': 0.09, 'max_depth': 1, 'n_estimators': 200}

0.843458 (0.056602) with: {'learning_rate': 0.09, 'max_depth': 3, 'n_estimators': 50}

0.855060 (0.056710) with: {'learning_rate': 0.09, 'max_depth': 3, 'n_estimators': 100}

0.858793 (0.055724) with: {'learning_rate': 0.09, 'max_depth': 3, 'n_estimators': 150}

0.860149 (0.055734) with: {'learning_rate': 0.09, 'max_depth': 3, 'n_estimators': 200}

0.842437 (0.046911) with: {'learning_rate': 0.09, 'max_depth': 5, 'n_estimators': 50}

0.849599 (0.045852) with: {'learning_rate': 0.09, 'max_depth': 5, 'n_estimators': 100}

0.850152 (0.046078) with: {'learning_rate': 0.09, 'max_depth': 5, 'n_estimators': 150}

0.849891 (0.046197) with: {'learning_rate': 0.09, 'max_depth': 5, 'n_estimators': 200}

0.807907 (0.051134) with: {'learning_rate': 0.09, 'max_depth': 7, 'n_estimators': 50}

0.810696 (0.051038) with: {'learning_rate': 0.09, 'max_depth': 7, 'n_estimators': 100}

0.810941 (0.050779) with: {'learning_rate': 0.09, 'max_depth': 7, 'n_estimators': 150}

0.810979 (0.050839) with: {'learning_rate': 0.09, 'max_depth': 7, 'n_estimators': 200}

0.804573 (0.052898) with: {'learning_rate': 0.09, 'max_depth': 9, 'n_estimators': 50}

0.809204 (0.053292) with: {'learning_rate': 0.09, 'max_depth': 9, 'n_estimators': 100}

0.809325 (0.053303) with: {'learning_rate': 0.09, 'max_depth': 9, 'n_estimators': 150}

0.809351 (0.053284) with: {'learning_rate': 0.09, 'max_depth': 9, 'n_estimators': 200}

0.804379 (0.051647) with: {'learning_rate': 0.09, 'max_depth': 11, 'n_estimators': 50}

0.807157 (0.053047) with: {'learning_rate': 0.09, 'max_depth': 11, 'n_estimators': 100}

0.807332 (0.053061) with: {'learning_rate': 0.09, 'max_depth': 11, 'n_estimators': 150}

0.807335 (0.053062) with: {'learning_rate': 0.09, 'max_depth': 11, 'n_estimators': 200}

0.809283 (0.050355) with: {'learning_rate': 0.09, 'max_depth': 13, 'n_estimators': 50}

0.812004 (0.052245) with: {'learning_rate': 0.09, 'max_depth': 13, 'n_estimators': 100}

0.812156 (0.052289) with: {'learning_rate': 0.09, 'max_depth': 13, 'n_estimators': 150}

0.812158 (0.052290) with: {'learning_rate': 0.09, 'max_depth': 13, 'n_estimators': 200}

0.808697 (0.047241) with: {'learning_rate': 0.09, 'max_depth': 15, 'n_estimators': 50}

0.811460 (0.049551) with: {'learning_rate': 0.09, 'max_depth': 15, 'n_estimators': 100}

0.811645 (0.049603) with: {'learning_rate': 0.09, 'max_depth': 15, 'n_estimators': 150}

0.811647 (0.049603) with: {'learning_rate': 0.09, 'max_depth': 15, 'n_estimators': 200}

0.797008 (0.044026) with: {'learning_rate': 0.12, 'max_depth': 1, 'n_estimators': 50}

0.819497 (0.048774) with: {'learning_rate': 0.12, 'max_depth': 1, 'n_estimators': 100}

0.828557 (0.049254) with: {'learning_rate': 0.12, 'max_depth': 1, 'n_estimators': 150}

0.831446 (0.048579) with: {'learning_rate': 0.12, 'max_depth': 1, 'n_estimators': 200}

0.850108 (0.054443) with: {'learning_rate': 0.12, 'max_depth': 3, 'n_estimators': 50}

0.860703 (0.051990) with: {'learning_rate': 0.12, 'max_depth': 3, 'n_estimators': 100}

0.862097 (0.050875) with: {'learning_rate': 0.12, 'max_depth': 3, 'n_estimators': 150}

0.862991 (0.050771) with: {'learning_rate': 0.12, 'max_depth': 3, 'n_estimators': 200}

0.845629 (0.050619) with: {'learning_rate': 0.12, 'max_depth': 5, 'n_estimators': 50}

0.846694 (0.051708) with: {'learning_rate': 0.12, 'max_depth': 5, 'n_estimators': 100}

0.846881 (0.051518) with: {'learning_rate': 0.12, 'max_depth': 5, 'n_estimators': 150}

0.847447 (0.051179) with: {'learning_rate': 0.12, 'max_depth': 5, 'n_estimators': 200}

0.818390 (0.048416) with: {'learning_rate': 0.12, 'max_depth': 7, 'n_estimators': 50}

0.820131 (0.048414) with: {'learning_rate': 0.12, 'max_depth': 7, 'n_estimators': 100}

0.820054 (0.048396) with: {'learning_rate': 0.12, 'max_depth': 7, 'n_estimators': 150}

0.820016 (0.048421) with: {'learning_rate': 0.12, 'max_depth': 7, 'n_estimators': 200}

0.804340 (0.057268) with: {'learning_rate': 0.12, 'max_depth': 9, 'n_estimators': 50}

0.806046 (0.057127) with: {'learning_rate': 0.12, 'max_depth': 9, 'n_estimators': 100}

0.806095 (0.057104) with: {'learning_rate': 0.12, 'max_depth': 9, 'n_estimators': 150}

0.806095 (0.057104) with: {'learning_rate': 0.12, 'max_depth': 9, 'n_estimators': 200}

0.810022 (0.052949) with: {'learning_rate': 0.12, 'max_depth': 11, 'n_estimators': 50}

0.810958 (0.053529) with: {'learning_rate': 0.12, 'max_depth': 11, 'n_estimators': 100}

0.810963 (0.053537) with: {'learning_rate': 0.12, 'max_depth': 11, 'n_estimators': 150}

0.810963 (0.053537) with: {'learning_rate': 0.12, 'max_depth': 11, 'n_estimators': 200}

0.807990 (0.050201) with: {'learning_rate': 0.12, 'max_depth': 13, 'n_estimators': 50}

0.809496 (0.050527) with: {'learning_rate': 0.12, 'max_depth': 13, 'n_estimators': 100}

0.809512 (0.050529) with: {'learning_rate': 0.12, 'max_depth': 13, 'n_estimators': 150}

0.809512 (0.050529) with: {'learning_rate': 0.12, 'max_depth': 13, 'n_estimators': 200}

0.810050 (0.051373) with: {'learning_rate': 0.12, 'max_depth': 15, 'n_estimators': 50}

0.811131 (0.052055) with: {'learning_rate': 0.12, 'max_depth': 15, 'n_estimators': 100}

0.811146 (0.052061) with: {'learning_rate': 0.12, 'max_depth': 15, 'n_estimators': 150}

0.811146 (0.052061) with: {'learning_rate': 0.12, 'max_depth': 15, 'n_estimators': 200}

0.807162 (0.048547) with: {'learning_rate': 0.15, 'max_depth': 1, 'n_estimators': 50}

0.824273 (0.050445) with: {'learning_rate': 0.15, 'max_depth': 1, 'n_estimators': 100}

0.830500 (0.050552) with: {'learning_rate': 0.15, 'max_depth': 1, 'n_estimators': 150}

0.830391 (0.051783) with: {'learning_rate': 0.15, 'max_depth': 1, 'n_estimators': 200}

0.852195 (0.056525) with: {'learning_rate': 0.15, 'max_depth': 3, 'n_estimators': 50}

0.858841 (0.055583) with: {'learning_rate': 0.15, 'max_depth': 3, 'n_estimators': 100}

0.860678 (0.055755) with: {'learning_rate': 0.15, 'max_depth': 3, 'n_estimators': 150}

0.860202 (0.056060) with: {'learning_rate': 0.15, 'max_depth': 3, 'n_estimators': 200}

0.851480 (0.042938) with: {'learning_rate': 0.15, 'max_depth': 5, 'n_estimators': 50}

0.852485 (0.043547) with: {'learning_rate': 0.15, 'max_depth': 5, 'n_estimators': 100}

0.852983 (0.043729) with: {'learning_rate': 0.15, 'max_depth': 5, 'n_estimators': 150}

0.853004 (0.043800) with: {'learning_rate': 0.15, 'max_depth': 5, 'n_estimators': 200}

0.811017 (0.051230) with: {'learning_rate': 0.15, 'max_depth': 7, 'n_estimators': 50}

0.811935 (0.051563) with: {'learning_rate': 0.15, 'max_depth': 7, 'n_estimators': 100}

0.812016 (0.051550) with: {'learning_rate': 0.15, 'max_depth': 7, 'n_estimators': 150}

0.812016 (0.051550) with: {'learning_rate': 0.15, 'max_depth': 7, 'n_estimators': 200}

0.807335 (0.054503) with: {'learning_rate': 0.15, 'max_depth': 9, 'n_estimators': 50}

0.807742 (0.054438) with: {'learning_rate': 0.15, 'max_depth': 9, 'n_estimators': 100}

0.807742 (0.054438) with: {'learning_rate': 0.15, 'max_depth': 9, 'n_estimators': 150}

0.807742 (0.054438) with: {'learning_rate': 0.15, 'max_depth': 9, 'n_estimators': 200}

0.810597 (0.052285) with: {'learning_rate': 0.15, 'max_depth': 11, 'n_estimators': 50}

0.810936 (0.052312) with: {'learning_rate': 0.15, 'max_depth': 11, 'n_estimators': 100}

0.810936 (0.052312) with: {'learning_rate': 0.15, 'max_depth': 11, 'n_estimators': 150}

0.810936 (0.052312) with: {'learning_rate': 0.15, 'max_depth': 11, 'n_estimators': 200}

0.814041 (0.049302) with: {'learning_rate': 0.15, 'max_depth': 13, 'n_estimators': 50}

0.814413 (0.049371) with: {'learning_rate': 0.15, 'max_depth': 13, 'n_estimators': 100}

0.814413 (0.049371) with: {'learning_rate': 0.15, 'max_depth': 13, 'n_estimators': 150}

0.814413 (0.049371) with: {'learning_rate': 0.15, 'max_depth': 13, 'n_estimators': 200}

0.807168 (0.053947) with: {'learning_rate': 0.15, 'max_depth': 15, 'n_estimators': 50}

0.807499 (0.054091) with: {'learning_rate': 0.15, 'max_depth': 15, 'n_estimators': 100}

0.807499 (0.054091) with: {'learning_rate': 0.15, 'max_depth': 15, 'n_estimators': 150}

0.807499 (0.054091) with: {'learning_rate': 0.15, 'max_depth': 15, 'n_estimators': 200}

0.810923 (0.050566) with: {'learning_rate': 0.18, 'max_depth': 1, 'n_estimators': 50}

0.826561 (0.050272) with: {'learning_rate': 0.18, 'max_depth': 1, 'n_estimators': 100}

0.830294 (0.049726) with: {'learning_rate': 0.18, 'max_depth': 1, 'n_estimators': 150}

0.830412 (0.050068) with: {'learning_rate': 0.18, 'max_depth': 1, 'n_estimators': 200}

0.847566 (0.059016) with: {'learning_rate': 0.18, 'max_depth': 3, 'n_estimators': 50}

0.854473 (0.056008) with: {'learning_rate': 0.18, 'max_depth': 3, 'n_estimators': 100}

0.855668 (0.056143) with: {'learning_rate': 0.18, 'max_depth': 3, 'n_estimators': 150}

0.855706 (0.055851) with: {'learning_rate': 0.18, 'max_depth': 3, 'n_estimators': 200}

0.841307 (0.052664) with: {'learning_rate': 0.18, 'max_depth': 5, 'n_estimators': 50}

0.841590 (0.053217) with: {'learning_rate': 0.18, 'max_depth': 5, 'n_estimators': 100}

0.841445 (0.053423) with: {'learning_rate': 0.18, 'max_depth': 5, 'n_estimators': 150}

0.841435 (0.053478) with: {'learning_rate': 0.18, 'max_depth': 5, 'n_estimators': 200}

0.807878 (0.052757) with: {'learning_rate': 0.18, 'max_depth': 7, 'n_estimators': 50}

0.808334 (0.052373) with: {'learning_rate': 0.18, 'max_depth': 7, 'n_estimators': 100}

0.808363 (0.052378) with: {'learning_rate': 0.18, 'max_depth': 7, 'n_estimators': 150}

0.808363 (0.052378) with: {'learning_rate': 0.18, 'max_depth': 7, 'n_estimators': 200}

0.804948 (0.054592) with: {'learning_rate': 0.18, 'max_depth': 9, 'n_estimators': 50}

0.805130 (0.054519) with: {'learning_rate': 0.18, 'max_depth': 9, 'n_estimators': 100}

0.805130 (0.054519) with: {'learning_rate': 0.18, 'max_depth': 9, 'n_estimators': 150}

0.805130 (0.054519) with: {'learning_rate': 0.18, 'max_depth': 9, 'n_estimators': 200}

0.803086 (0.052977) with: {'learning_rate': 0.18, 'max_depth': 11, 'n_estimators': 50}

0.803229 (0.052990) with: {'learning_rate': 0.18, 'max_depth': 11, 'n_estimators': 100}

0.803229 (0.052990) with: {'learning_rate': 0.18, 'max_depth': 11, 'n_estimators': 150}

0.803229 (0.052990) with: {'learning_rate': 0.18, 'max_depth': 11, 'n_estimators': 200}

0.806149 (0.054086) with: {'learning_rate': 0.18, 'max_depth': 13, 'n_estimators': 50}

0.806294 (0.054156) with: {'learning_rate': 0.18, 'max_depth': 13, 'n_estimators': 100}

0.806294 (0.054156) with: {'learning_rate': 0.18, 'max_depth': 13, 'n_estimators': 150}

0.806294 (0.054156) with: {'learning_rate': 0.18, 'max_depth': 13, 'n_estimators': 200}

0.805339 (0.054438) with: {'learning_rate': 0.18, 'max_depth': 15, 'n_estimators': 50}

0.805497 (0.054478) with: {'learning_rate': 0.18, 'max_depth': 15, 'n_estimators': 100}

0.805497 (0.054478) with: {'learning_rate': 0.18, 'max_depth': 15, 'n_estimators': 150}

0.805497 (0.054478) with: {'learning_rate': 0.18, 'max_depth': 15, 'n_estimators': 200}

0.818772 (0.048965) with: {'learning_rate': 0.21, 'max_depth': 1, 'n_estimators': 50}

0.830305 (0.048710) with: {'learning_rate': 0.21, 'max_depth': 1, 'n_estimators': 100}

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