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Commit a2863cd7 authored by Martyna Plomecka's avatar Martyna Plomecka
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Merrged conflicts

parents 83e6e3e2 9e41be14
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SimpleClassifiers/sklearnclassifier.py
View file @ a2863cd7
......@@ -39,12 +39,12 @@ def cross_validate_SVC(X, y):
def cross_validate_RFC(X, y):
logging.info("Cross-validation RFC...")
classifier = RandomForestClassifier(max_features='auto', random_state=42, n_jobs=-1)
parameters_RFC = {'n_estimators': [10, 100, 1000, 5000], 'max_depth': [5, 10, 50, 100, 500]}
parameters_RFC = {'n_estimators': [10, 50, 100, 1000], 'max_depth': [5, 10, 50, 100, 500], 'min_samples_split' : [0.1, 0.4, 0.7, 1.0], 'min_samples_leaf' : [0.1, 0.5]}
cross_validate(classifier=classifier, parameters=parameters_RFC, X=X, y=y)
def cross_validate(classifier, parameters, X, y):
X = X.reshape((36223, 500 * 129))
clf = GridSearchCV(classifier, parameters, scoring='accuracy', n_jobs=-1, verbose=3)
clf = GridSearchCV(classifier, parameters, scoring='accuracy', n_jobs=-1, verbose=3, cv=2)
clf.fit(X, y.ravel())
export_dict(clf.cv_results_['mean_fit_time'], clf.cv_results_['std_fit_time'], clf.cv_results_['mean_score_time'],
......@@ -58,17 +58,19 @@ def cross_validate(classifier, parameters, X, y):
def try_sklearn_classifiers(X, y):
logging.info("Training the simple classifiers: kNN, Linear SVM, Random Forest and Naive Bayes.")
names = ["Nearest Neighbors",
"Linear SVM",
names = [# "Nearest Neighbors",
# "Linear SVM",
"Random Forest",
"Naive Bayes",
"Linear SVM"
]
classifiers = [
KNeighborsClassifier(n_neighbors=100, weights='uniform', algorithm='auto', leaf_size=100, n_jobs=-1),
LinearSVC(tol=1e-5, C=1, random_state=42, max_iter=10000),
RandomForestClassifier(n_estimators=1000, max_depth=50, max_features='auto', random_state=42, n_jobs=-1),
GaussianNB()
# KNeighborsClassifier(n_neighbors=5, weights='uniform', algorithm='auto', leaf_size=30, n_jobs=-1),
# LinearSVC(tol=1e-5, C=1, random_state=42, max_iter=1000),
RandomForestClassifier(n_estimators=30, max_depth=20, max_features='auto', random_state=42, n_jobs=-1),
GaussianNB(),
LinearSVC(tol=1e-3, C=5, random_state=42, max_iter=500)
]
X = X.reshape((36223, 500 * 129))
......
main.py
View file @ a2863cd7
......@@ -51,7 +51,7 @@ def main():
try_sklearn_classifiers(trainX, trainY)
# cross_validate_kNN(trainX, trainY)
# cross_validate_SVC(trainX, trainY)
# cross_validate_RFC(trainX, trainY)
cross_validate_RFC(trainX, trainY)
else:
# tune(trainX,trainY)
run(trainX,trainY)
......
results/ETRA/simple_classifiers/CV_RandomForest/CrossValidation_results.csv 0 → 100644
View file @ a2863cd7
mean_fit_time,std_fit_time,mean_score_time,std_score_time,mean_test_score,std_test_score,params
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47.891690373420715,0.3733121156692505,5.038571357727051,0.22652125358581543,0.6565717591318982,0.0011689652497272052,"{'max_depth': 5, 'min_samples_leaf': 0.1, 'min_samples_split': 0.1, 'n_estimators': 50}"
122.98335754871368,13.516207337379456,24.53887927532196,14.744704127311707,0.6587803433474532,0.0003770747962164034,"{'max_depth': 5, 'min_samples_leaf': 0.1, 'min_samples_split': 0.1, 'n_estimators': 100}"
883.4977535009384,80.00896108150482,9.427534699440002,0.3770390748977661,0.6598846369794981,0.0012053083575899182,"{'max_depth': 5, 'min_samples_leaf': 0.1, 'min_samples_split': 0.1, 'n_estimators': 1000}"
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409.52198326587677,36.71951115131378,22.855531454086304,17.405255794525146,0.6389034725713811,0.0004869531367521218,"{'max_depth': 5, 'min_samples_leaf': 0.1, 'min_samples_split': 0.4, 'n_estimators': 1000}"
64.51970708370209,47.177589535713196,7.125189661979675,0.6362177133560181,0.5187864068222405,1.4322016586743036e-05,"{'max_depth': 5, 'min_samples_leaf': 0.1, 'min_samples_split': 0.7, 'n_estimators': 10}"
13.957017064094543,0.008815407752990723,14.087352514266968,9.406677484512329,0.5187864068222405,1.4322016586743036e-05,"{'max_depth': 5, 'min_samples_leaf': 0.1, 'min_samples_split': 0.7, 'n_estimators': 50}"
21.921236991882324,8.11500072479248,7.836744666099548,2.1957043409347534,0.5187864068222405,1.4322016586743036e-05,"{'max_depth': 5, 'min_samples_leaf': 0.1, 'min_samples_split': 0.7, 'n_estimators': 100}"
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20.824050903320312,0.007511138916015625,4.722916603088379,0.0834496021270752,0.5187864068222405,1.4322016586743036e-05,"{'max_depth': 500, 'min_samples_leaf': 0.5, 'min_samples_split': 0.1, 'n_estimators': 1000}"
17.814435482025146,0.0776064395904541,5.555830240249634,0.9946925640106201,0.5187864068222405,1.4322016586743036e-05,"{'max_depth': 500, 'min_samples_leaf': 0.5, 'min_samples_split': 0.4, 'n_estimators': 10}"
17.674492955207825,0.1324857473373413,5.178620338439941,1.1328403949737549,0.5187864068222405,1.4322016586743036e-05,"{'max_depth': 500, 'min_samples_leaf': 0.5, 'min_samples_split': 0.4, 'n_estimators': 50}"
17.79864728450775,0.15510261058807373,3.9749338626861572,0.16785120964050293,0.5187864068222405,1.4322016586743036e-05,"{'max_depth': 500, 'min_samples_leaf': 0.5, 'min_samples_split': 0.4, 'n_estimators': 100}"
20.824003100395203,0.15394270420074463,5.66940975189209,1.1961572170257568,0.5187864068222405,1.4322016586743036e-05,"{'max_depth': 500, 'min_samples_leaf': 0.5, 'min_samples_split': 0.4, 'n_estimators': 1000}"
17.45400846004486,0.09665381908416748,4.216432213783264,0.030864357948303223,0.5187864068222405,1.4322016586743036e-05,"{'max_depth': 500, 'min_samples_leaf': 0.5, 'min_samples_split': 0.7, 'n_estimators': 10}"
17.23139774799347,0.4188793897628784,4.150138020515442,0.08017909526824951,0.5187864068222405,1.4322016586743036e-05,"{'max_depth': 500, 'min_samples_leaf': 0.5, 'min_samples_split': 0.7, 'n_estimators': 50}"
18.135766863822937,0.1738947629928589,4.036443114280701,0.1694260835647583,0.5187864068222405,1.4322016586743036e-05,"{'max_depth': 500, 'min_samples_leaf': 0.5, 'min_samples_split': 0.7, 'n_estimators': 100}"
21.967405438423157,0.07662022113800049,6.043361306190491,1.364613652229309,0.5187864068222405,1.4322016586743036e-05,"{'max_depth': 500, 'min_samples_leaf': 0.5, 'min_samples_split': 0.7, 'n_estimators': 1000}"
17.738407969474792,0.27931487560272217,4.150700092315674,0.06198549270629883,0.5187864068222405,1.4322016586743036e-05,"{'max_depth': 500, 'min_samples_leaf': 0.5, 'min_samples_split': 1.0, 'n_estimators': 10}"
17.846079349517822,0.2303450107574463,4.350938081741333,0.06318497657775879,0.5187864068222405,1.4322016586743036e-05,"{'max_depth': 500, 'min_samples_leaf': 0.5, 'min_samples_split': 1.0, 'n_estimators': 50}"
18.38229274749756,0.4923088550567627,5.322735667228699,1.2695757150650024,0.5187864068222405,1.4322016586743036e-05,"{'max_depth': 500, 'min_samples_leaf': 0.5, 'min_samples_split': 1.0, 'n_estimators': 100}"
19.55625057220459,0.6858994960784912,3.9001559019088745,0.1318424940109253,0.5187864068222405,1.4322016586743036e-05,"{'max_depth': 500, 'min_samples_leaf': 0.5, 'min_samples_split': 1.0, 'n_estimators': 1000}"
results/ETRA/simple_classifiers/CV_RandomForest/best_results.csv 0 → 100644
View file @ a2863cd7
BEST ESTIMATOR,BEST SCORE,BEST PARAMS
"RandomForestClassifier(max_depth=5, min_samples_leaf=0.1, min_samples_split=0.1,
n_estimators=1000, n_jobs=-1, random_state=42)",0.6598846369794981,"{'max_depth': 5, 'min_samples_leaf': 0.1, 'min_samples_split': 0.1, 'n_estimators': 1000}"
results/ETRA/simple_classifiers/CV_RandomForest/console.out 0 → 100644
View file @ a2863cd7
(36223, 500, 129)
(36223, 1)
Fitting 2 folds for each of 160 candidates, totalling 320 fits
results/ETRA/simple_classifiers/CV_RandomForest/info.log 0 → 100644
View file @ a2863cd7
INFO:root:Started the Logging
INFO:root:X training loaded.
INFO:root:(129, 500, 36223)
INFO:root:y training loaded.
INFO:root:(1, 36223)
INFO:root:Setting the shapes
INFO:root:(36223, 500, 129)
INFO:root:(36223, 1)
INFO:root:Cross-validation RFC...
INFO:root:--- Runtime: 6324.672133684158 seconds ---
INFO:root:Finished Logging
results/ETRA/simple_classifiers/CV_RandomForest/lsf.o166818966 0 → 100644
View file @ a2863cd7
Sender: LSF System <lsfadmin@eu-g1-047-3>
Subject: Job 166818966: <python /cluster/home/mplomecka/dl-project/main.py> in cluster <euler> Done
Job <python /cluster/home/mplomecka/dl-project/main.py> was submitted from host <eu-login-16> by user <mplomecka> in cluster <euler> at Tue Mar 23 22:48:07 2021
Job was executed on host(s) <5*eu-g1-047-3>, in queue <bigmem.24h>, as user <mplomecka> in cluster <euler> at Tue Mar 23 22:48:25 2021
</cluster/home/mplomecka> was used as the home directory.
</cluster/home/mplomecka/dl-project> was used as the working directory.
Started at Tue Mar 23 22:48:25 2021
Terminated at Wed Mar 24 00:34:06 2021
Results reported at Wed Mar 24 00:34:06 2021
Your job looked like:
------------------------------------------------------------
# LSBATCH: User input
python /cluster/home/mplomecka/dl-project/main.py
------------------------------------------------------------
Successfully completed.
Resource usage summary:
CPU time : 30735.00 sec.
Max Memory : 178567 MB
Average Memory : 146656.00 MB
Total Requested Memory : 125000.00 MB
Delta Memory : -53567.00 MB
Max Swap : -
Max Processes : 10
Max Threads : 52
Run time : 6347 sec.
Turnaround time : 6359 sec.
The output (if any) follows:
2021-03-23 22:48:27.263584: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
(36223, 500, 129)
(36223, 1)
Fitting 2 folds for each of 160 candidates, totalling 320 fits
[Parallel(n_jobs=-1)]: Using backend LokyBackend with 5 concurrent workers.
[CV] max_depth=5, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=10
[CV] max_depth=5, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=10, score=0.654, total= 48.8s
[CV] max_depth=5, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=100
[CV] max_depth=5, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=100, score=0.659, total= 2.5min
[CV] max_depth=5, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=100
[CV] max_depth=5, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=100, score=0.633, total= 48.3s
[CV] max_depth=5, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=1000
[CV] max_depth=5, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=1000, score=0.638, total= 6.3min
[CV] max_depth=5, min_samples_leaf=0.1, min_samples_split=0.7, n_estimators=1000
[CV] max_depth=5, min_samples_leaf=0.1, min_samples_split=0.7, n_estimators=1000, score=0.519, total= 2.1min
[CV] max_depth=5, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=10
[CV] max_depth=5, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=10, score=0.519, total= 17.7s
[CV] max_depth=5, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=50
[CV] max_depth=5, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=50, score=0.519, total= 1.2min
[CV] max_depth=5, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=10
[CV] max_depth=5, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=10, score=0.519, total= 1.3min
[CV] max_depth=5, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=50
[CV] max_depth=5, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=50, score=0.519, total= 39.0s
[CV] max_depth=5, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=1000
[CV] max_depth=5, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=1000, score=0.519, total= 51.7s
[CV] max_depth=5, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=1000
[CV] max_depth=5, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=1000, score=0.519, total= 27.8s
[CV] max_depth=5, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=50
[CV] max_depth=5, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=50, score=0.519, total= 25.8s
[CV] max_depth=10, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=10
[CV] max_depth=10, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=10, score=0.646, total= 28.0s
[CV] max_depth=10, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=100
[CV] max_depth=10, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=100, score=0.659, total= 2.2min
[CV] max_depth=10, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=50
[CV] max_depth=10, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=50, score=0.632, total= 1.1min
[CV] max_depth=10, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=1000
[CV] max_depth=10, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=1000, score=0.638, total= 6.8min
[CV] max_depth=10, min_samples_leaf=0.1, min_samples_split=0.7, n_estimators=1000
[CV] max_depth=10, min_samples_leaf=0.1, min_samples_split=0.7, n_estimators=1000, score=0.519, total= 58.9s
[CV] max_depth=10, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=10
[CV] max_depth=10, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=10, score=0.519, total= 54.1s
[CV] max_depth=10, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=50
[CV] max_depth=10, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=50, score=0.519, total= 44.7s
[CV] max_depth=10, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=100
[CV] max_depth=10, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=100, score=0.519, total= 48.1s
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=10
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=10, score=0.519, total= 47.8s
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=50
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=50, score=0.519, total= 36.3s
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=1000
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=1000, score=0.519, total= 37.7s
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=50
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=50, score=0.519, total= 24.1s
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=100
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=100, score=0.519, total= 36.4s
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=10
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=10, score=0.519, total= 33.0s
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=100
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=100, score=0.519, total= 22.3s
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=10
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=10, score=0.519, total= 20.8s
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=100
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=100, score=0.519, total= 22.2s
[CV] max_depth=50, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=50
[CV] max_depth=50, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=50, score=0.658, total= 1.0min
[CV] max_depth=50, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=10
[CV] max_depth=50, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=10, score=0.614, total= 23.9s
[CV] max_depth=50, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=10
[CV] max_depth=50, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=10, score=0.615, total= 47.0s
[CV] max_depth=50, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=50
[CV] max_depth=50, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=50, score=0.628, total= 2.2min
[CV] max_depth=50, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=1000
[CV] max_depth=50, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=1000, score=0.638, total= 8.5min
[CV] max_depth=50, min_samples_leaf=0.1, min_samples_split=0.7, n_estimators=1000
[CV] max_depth=50, min_samples_leaf=0.1, min_samples_split=0.7, n_estimators=1000, score=0.519, total= 37.7s
[CV] max_depth=50, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=10
[CV] max_depth=50, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=10, score=0.519, total= 1.0min
[CV] max_depth=50, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=50
[CV] max_depth=50, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=50, score=0.519, total= 44.0s
[CV] max_depth=50, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=1000
[CV] max_depth=50, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=1000, score=0.519, total= 29.8s
[CV] max_depth=50, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=50
[CV] max_depth=50, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=50, score=0.519, total= 22.5s
[CV] max_depth=50, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=1000
[CV] max_depth=50, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=1000, score=0.519, total= 26.4s
[CV] max_depth=50, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=100
[CV] max_depth=50, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=100, score=0.519, total= 21.9s
[CV] max_depth=50, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=50
[CV] max_depth=50, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=50, score=0.519, total= 22.9s
[CV] max_depth=50, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=1000
[CV] max_depth=50, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=1000, score=0.519, total= 26.7s
[CV] max_depth=50, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=100
[CV] max_depth=50, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=100, score=0.519, total= 23.0s
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=10
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=10, score=0.646, total= 33.3s
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=100
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=100, score=0.659, total= 3.1min
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=50
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=50, score=0.632, total= 1.3min
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=100
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=100, score=0.637, total= 1.3min
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=0.7, n_estimators=10
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=0.7, n_estimators=10, score=0.519, total= 1.1min
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=0.7, n_estimators=10
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=0.7, n_estimators=10, score=0.519, total= 33.2s
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=0.7, n_estimators=50
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=0.7, n_estimators=50, score=0.519, total= 2.1min
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=0.7, n_estimators=50
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=0.7, n_estimators=50, score=0.519, total= 33.7s
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=0.7, n_estimators=100
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=0.7, n_estimators=100, score=0.519, total= 33.2s
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=0.7, n_estimators=100
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=0.7, n_estimators=100, score=0.519, total= 25.8s
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=0.7, n_estimators=1000
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=0.7, n_estimators=1000, score=0.519, total= 37.2s
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=0.7, n_estimators=1000
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=0.7, n_estimators=1000, score=0.519, total= 1.8min
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=10
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=10, score=0.519, total= 39.6s
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=50
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=50, score=0.519, total= 36.1s
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=100
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=100, score=0.519, total= 28.9s
[CV] max_depth=100, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=10
[CV] max_depth=100, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=10, score=0.519, total= 21.6s
[CV] max_depth=100, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=1000
[CV] max_depth=100, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=1000, score=0.519, total= 25.7s
[CV] max_depth=100, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=50
[CV] max_depth=100, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=50, score=0.519, total= 22.4s
[CV] max_depth=100, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=10
[CV] max_depth=100, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=10, score=0.519, total= 22.0s
[CV] max_depth=100, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=100
[CV] max_depth=100, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=100, score=0.519, total= 22.9s
[CV] max_depth=100, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=50
[CV] max_depth=100, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=50, score=0.519, total= 24.1s
[CV] max_depth=100, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=1000
[CV] max_depth=100, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=1000, score=0.519, total= 24.4s
[CV] max_depth=500, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=100
[CV] max_depth=500, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=100, score=0.658, total= 2.2min
[CV] max_depth=500, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=50
[CV] max_depth=500, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=50, score=0.628, total= 49.5s
[CV] max_depth=500, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=50
[CV] max_depth=500, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=50, score=0.632, total= 43.3s
[CV] max_depth=500, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=1000
[CV] max_depth=500, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=1000, score=0.638, total= 8.4min
[CV] max_depth=500, min_samples_leaf=0.1, min_samples_split=0.7, n_estimators=100
[CV] max_depth=500, min_samples_leaf=0.1, min_samples_split=0.7, n_estimators=100, score=0.519, total= 1.6min
[CV] max_depth=500, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=10
[CV] max_depth=500, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=10, score=0.519, total= 40.4s
[CV] max_depth=500, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=100
[CV] max_depth=500, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=100, score=0.519, total= 36.8s
[CV] max_depth=500, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=1000
[CV] max_depth=500, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=1000, score=0.519, total= 28.1s
[CV] max_depth=500, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=50
[CV] max_depth=500, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=50, score=0.519, total= 19.7s
[CV] max_depth=500, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=1000
[CV] max_depth=500, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=1000, score=0.519, total= 25.6s
[CV] max_depth=500, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=100
[CV] max_depth=500, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=100, score=0.519, total= 21.8s
[CV] max_depth=500, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=10
[CV] max_depth=500, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=10, score=0.519, total= 21.5s
[CV] max_depth=500, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=1000
[CV] max_depth=500, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=1000, score=0.519, total= 26.6s
[CV] max_depth=500, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=50
[CV] max_depth=500, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=50, score=0.519, total= 22.5s
[CV] max_depth=5, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=10
[CV] max_depth=5, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=10, score=0.646, total= 1.4min
[CV] max_depth=5, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=10
[CV] max_depth=5, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=10, score=0.614, total= 27.0s
[CV] max_depth=5, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=10
[CV] max_depth=5, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=10, score=0.615, total= 3.0min
[CV] max_depth=5, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=1000
[CV] max_depth=5, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=1000, score=0.639, total= 8.1min
[CV] max_depth=5, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=50
[CV] max_depth=5, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=50, score=0.519, total= 17.5s
[CV] max_depth=5, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=100
[CV] max_depth=5, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=100, score=0.519, total= 19.7s
[CV] max_depth=5, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=1000
[CV] max_depth=5, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=1000, score=0.519, total= 20.1s
[CV] max_depth=5, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=10
[CV] max_depth=5, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=10, score=0.519, total= 18.8s
[CV] max_depth=5, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=100
[CV] max_depth=5, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=100, score=0.519, total= 19.5s
[CV] max_depth=5, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=1000
[CV] max_depth=5, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=1000, score=0.519, total= 57.3s
[CV] max_depth=5, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=1000
[CV] max_depth=5, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=1000, score=0.519, total= 59.0s
[CV] max_depth=5, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=50
[CV] max_depth=5, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=50, score=0.519, total= 23.7s
[CV] max_depth=5, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=1000
[CV] max_depth=5, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=1000, score=0.519, total= 28.1s
[CV] max_depth=5, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=100
[CV] max_depth=5, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=100, score=0.519, total= 26.5s
[CV] max_depth=10, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=50
[CV] max_depth=10, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=50, score=0.655, total= 1.0min
[CV] max_depth=10, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=1000
[CV] max_depth=10, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=1000, score=0.661, total=12.0min
[CV] max_depth=10, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=100
[CV] max_depth=10, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=100, score=0.519, total= 52.7s
[CV] max_depth=10, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=1000
[CV] max_depth=10, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=1000, score=0.519, total= 51.9s
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=50
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=50, score=0.519, total= 34.4s
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=100
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=100, score=0.519, total= 37.0s
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=10
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=10, score=0.519, total= 21.5s
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=50
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=50, score=0.519, total= 23.7s
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=100
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=100, score=0.519, total= 37.8s
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=10
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=10, score=0.519, total= 23.0s
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=1000
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=1000, score=0.519, total= 27.2s
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=50
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=50, score=0.519, total= 21.6s
[CV] max_depth=50, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=10
[CV] max_depth=50, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=10, score=0.646, total= 53.8s
[CV] max_depth=50, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=1000
[CV] max_depth=50, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=1000, score=0.659, total=15.6min
[CV] max_depth=50, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=100
[CV] max_depth=50, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=100, score=0.519, total= 24.3s
[CV] max_depth=50, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=50
[CV] max_depth=50, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=50, score=0.519, total= 25.4s
[CV] max_depth=50, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=1000
[CV] max_depth=50, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=1000, score=0.519, total= 25.8s
[CV] max_depth=50, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=100
[CV] max_depth=50, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=100, score=0.519, total= 23.1s
[CV] max_depth=50, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=10
[CV] max_depth=50, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=10, score=0.519, total= 23.3s
[CV] max_depth=50, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=1000
[CV] max_depth=50, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=1000, score=0.519, total= 27.9s
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=50
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=50, score=0.655, total= 2.5min
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=10
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=10, score=0.615, total= 48.5s
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=50
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=50, score=0.628, total= 1.7min
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=1000
[CV] max_depth=100, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=1000, score=0.638, total=11.0min
[CV] max_depth=100, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=10
[CV] max_depth=100, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=10, score=0.519, total= 23.8s
[CV] max_depth=100, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=100
[CV] max_depth=100, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=100, score=0.519, total= 25.2s
[CV] max_depth=100, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=50
[CV] max_depth=100, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=50, score=0.519, total= 21.6s
[CV] max_depth=100, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=1000
[CV] max_depth=100, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=1000, score=0.519, total= 25.0s
[CV] max_depth=100, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=100
[CV] max_depth=100, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=100, score=0.519, total= 23.2s
[CV] max_depth=100, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=10
[CV] max_depth=100, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=10, score=0.519, total= 23.6s
[CV] max_depth=100, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=1000
[CV] max_depth=100, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=1000, score=0.519, total= 25.5s
[CV] max_depth=500, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=50
[CV] max_depth=500, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=50, score=0.655, total= 1.9min
[CV] max_depth=500, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=10
[CV] max_depth=500, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=10, score=0.614, total= 1.0min
[CV] max_depth=500, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=100
[CV] max_depth=500, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=100, score=0.637, total= 41.2s
[CV] max_depth=500, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=1000
[CV] max_depth=500, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=1000, score=0.639, total= 8.3min
[CV] max_depth=500, min_samples_leaf=0.1, min_samples_split=0.7, n_estimators=100
[CV] max_depth=500, min_samples_leaf=0.1, min_samples_split=0.7, n_estimators=100, score=0.519, total= 1.7min
[CV] max_depth=500, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=10
[CV] max_depth=500, min_samples_leaf=0.1, min_samples_split=1.0, n_estimators=10, score=0.519, total= 1.2min
[CV] max_depth=500, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=10
[CV] max_depth=500, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=10, score=0.519, total= 23.5s
[CV] max_depth=500, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=100
[CV] max_depth=500, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=100, score=0.519, total= 20.1s
[CV] max_depth=500, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=1000
[CV] max_depth=500, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=1000, score=0.519, total= 25.5s
[CV] max_depth=500, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=100
[CV] max_depth=500, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=100, score=0.519, total= 21.8s
[CV] max_depth=500, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=10
[CV] max_depth=500, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=10, score=0.519, total= 21.8s
[CV] max_depth=500, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=1000
[CV] max_depth=500, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=1000, score=0.519, total= 29.5s
[CV] max_depth=500, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=100
[CV] max_depth=500, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=100, score=0.519, total= 25.5s
[CV] max_depth=5, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=50
[CV] max_depth=5, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=50, score=0.658, total= 53.5s
[CV] max_depth=5, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=1000
[CV] max_depth=5, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=1000, score=0.661, total=16.2min
[CV] max_depth=5, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=100
[CV] max_depth=5, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=100, score=0.519, total= 24.9s
[CV] max_depth=5, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=50
[CV] max_depth=5, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=50, score=0.519, total= 25.2s
[CV] max_depth=5, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=1000
[CV] max_depth=5, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=1000, score=0.519, total= 28.3s
[CV] max_depth=10, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=100
[CV] max_depth=10, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=100, score=0.658, total= 1.8min
[CV] max_depth=10, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=10
[CV] max_depth=10, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=10, score=0.615, total= 54.7s
[CV] max_depth=10, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=100
[CV] max_depth=10, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=100, score=0.633, total= 1.6min
[CV] max_depth=10, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=1000
[CV] max_depth=10, min_samples_leaf=0.1, min_samples_split=0.4, n_estimators=1000, score=0.639, total=11.2min
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=1000
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.1, n_estimators=1000, score=0.519, total= 1.2min
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=1000
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.4, n_estimators=1000, score=0.519, total= 42.6s
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=50
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=50, score=0.519, total= 24.9s
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=1000
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=0.7, n_estimators=1000, score=0.519, total= 24.4s
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=100
[CV] max_depth=10, min_samples_leaf=0.5, min_samples_split=1.0, n_estimators=100, score=0.519, total= 22.3s
[CV] max_depth=50, min_samples_leaf=0.1, min_samples_split=0.1, n_estimators=10