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randomforest_tuning.txt
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criterion=gini,n_estimators=50,max_features=1 -> mean_macro_f1_score=0.8150136925404992,deceased_f1score=0.7294147046682057,accuracy=0.8198258665714221
criterion=gini,n_estimators=50,max_features=2 -> mean_macro_f1_score=0.8156660073405828,deceased_f1score=0.7304317157789292,accuracy=0.8204024219531991
criterion=gini,n_estimators=50,max_features=3 -> mean_macro_f1_score=0.8155120830777107,deceased_f1score=0.7303376452170739,accuracy=0.8202377112264131
criterion=gini,n_estimators=50,max_features=4 -> mean_macro_f1_score=0.8151214020911279,deceased_f1score=0.7302632352557803,accuracy=0.8198258750511753
criterion=gini,n_estimators=100,max_features=1 -> mean_macro_f1_score=0.8153279628980364,deceased_f1score=0.7294036085533686,accuracy=0.8201141866610768
criterion=gini,n_estimators=100,max_features=2 -> mean_macro_f1_score=0.8156672860312512,deceased_f1score=0.7303850836168241,accuracy=0.8204024304329524
criterion=gini,n_estimators=100,max_features=3 -> mean_macro_f1_score=0.8155120830777107,deceased_f1score=0.7303376452170739,accuracy=0.8202377112264131
criterion=gini,n_estimators=100,max_features=4 -> mean_macro_f1_score=0.8151214020911279,deceased_f1score=0.7302632352557803,accuracy=0.8198258750511753
criterion=gini,n_estimators=150,max_features=1 -> mean_macro_f1_score=0.8157360313289006,deceased_f1score=0.7303827236980176,accuracy=0.8204847942760987
criterion=gini,n_estimators=150,max_features=2 -> mean_macro_f1_score=0.8156672860312512,deceased_f1score=0.7303850836168241,accuracy=0.8204024304329524
criterion=gini,n_estimators=150,max_features=3 -> mean_macro_f1_score=0.8155120830777107,deceased_f1score=0.7303376452170739,accuracy=0.8202377112264131
criterion=gini,n_estimators=150,max_features=4 -> mean_macro_f1_score=0.8151214020911279,deceased_f1score=0.7302632352557803,accuracy=0.8198258750511753
criterion=gini,n_estimators=200,max_features=1 -> mean_macro_f1_score=0.8156116631844395,deceased_f1score=0.7304293855432302,accuracy=0.8203612273119962
criterion=gini,n_estimators=200,max_features=2 -> mean_macro_f1_score=0.8156672860312512,deceased_f1score=0.7303850836168241,accuracy=0.8204024304329524
criterion=gini,n_estimators=200,max_features=3 -> mean_macro_f1_score=0.8155120830777107,deceased_f1score=0.7303376452170739,accuracy=0.8202377112264131
criterion=gini,n_estimators=200,max_features=4 -> mean_macro_f1_score=0.8151214020911279,deceased_f1score=0.7302632352557803,accuracy=0.8198258750511753
criterion=entropy,n_estimators=50,max_features=1 -> mean_macro_f1_score=0.8149849710468693,deceased_f1score=0.7295087333823995,accuracy=0.8197846888897257
criterion=entropy,n_estimators=50,max_features=2 -> mean_macro_f1_score=0.8155571225615914,deceased_f1score=0.7302875075520214,accuracy=0.8202788804283564
criterion=entropy,n_estimators=50,max_features=3 -> mean_macro_f1_score=0.8155235001643486,deceased_f1score=0.730515640911569,accuracy=0.8202377027466599
criterion=entropy,n_estimators=50,max_features=4 -> mean_macro_f1_score=0.8153298056812126,deceased_f1score=0.7303349953227495,accuracy=0.8200317804191644
criterion=entropy,n_estimators=100,max_features=1 -> mean_macro_f1_score=0.8152111212253386,deceased_f1score=0.7293513268318219,accuracy=0.8199906281767275
criterion=entropy,n_estimators=100,max_features=2 -> mean_macro_f1_score=0.8155571225615914,deceased_f1score=0.7302875075520214,accuracy=0.8202788804283564
criterion=entropy,n_estimators=100,max_features=3 -> mean_macro_f1_score=0.8155235001643486,deceased_f1score=0.730515640911569,accuracy=0.8202377027466599
criterion=entropy,n_estimators=100,max_features=4 -> mean_macro_f1_score=0.8153298056812126,deceased_f1score=0.7303349953227495,accuracy=0.8200317804191644
criterion=entropy,n_estimators=150,max_features=1 -> mean_macro_f1_score=0.8158196781109407,deceased_f1score=0.7304781573884941,accuracy=0.8205671411597384
criterion=entropy,n_estimators=150,max_features=2 -> mean_macro_f1_score=0.8155571225615914,deceased_f1score=0.7302875075520214,accuracy=0.8202788804283564
criterion=entropy,n_estimators=150,max_features=3 -> mean_macro_f1_score=0.8155235001643486,deceased_f1score=0.730515640911569,accuracy=0.8202377027466599
criterion=entropy,n_estimators=150,max_features=4 -> mean_macro_f1_score=0.8153298056812126,deceased_f1score=0.7303349953227495,accuracy=0.8200317804191644
criterion=entropy,n_estimators=200,max_features=1 -> mean_macro_f1_score=0.8157469714473884,deceased_f1score=0.7305612455591366,accuracy=0.8204847688368389
criterion=entropy,n_estimators=200,max_features=2 -> mean_macro_f1_score=0.8155571225615914,deceased_f1score=0.7302875075520214,accuracy=0.8202788804283564
criterion=entropy,n_estimators=200,max_features=3 -> mean_macro_f1_score=0.8155235001643486,deceased_f1score=0.730515640911569,accuracy=0.8202377027466599
criterion=entropy,n_estimators=200,max_features=4 -> mean_macro_f1_score=0.8153298056812126,deceased_f1score=0.7303349953227495,accuracy=0.8200317804191644