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uncommented models for logo

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Tanushree Tunstall 2022-07-10 12:53:51 +01:00
parent 4d5b848471
commit 9594d0a328
1 changed files with 28 additions and 28 deletions
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scripts/ml/ml_functions/MultClfs_logo_skf.py
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@ -261,34 +261,34 @@ def MultModelsCl_logo_skf(input_df
#====================================================== #======================================================
models = [('AdaBoost Classifier' , AdaBoostClassifier(**rs) ) models = [('AdaBoost Classifier' , AdaBoostClassifier(**rs) )
, ('Bagging Classifier' , BaggingClassifier(**rs, **njobs, bootstrap = True, oob_score = True, verbose = 3, n_estimators = 100) ) , ('Bagging Classifier' , BaggingClassifier(**rs, **njobs, bootstrap = True, oob_score = True, verbose = 3, n_estimators = 100) )
# , ('Decision Tree' , DecisionTreeClassifier(**rs) ) , ('Decision Tree' , DecisionTreeClassifier(**rs) )
# , ('Extra Tree' , ExtraTreeClassifier(**rs) ) , ('Extra Tree' , ExtraTreeClassifier(**rs) )
# , ('Extra Trees' , ExtraTreesClassifier(**rs) ) , ('Extra Trees' , ExtraTreesClassifier(**rs) )
# , ('Gradient Boosting' , GradientBoostingClassifier(**rs) ) , ('Gradient Boosting' , GradientBoostingClassifier(**rs) )
# , ('Gaussian NB' , GaussianNB() ) , ('Gaussian NB' , GaussianNB() )
# , ('Gaussian Process' , GaussianProcessClassifier(**rs) ) , ('Gaussian Process' , GaussianProcessClassifier(**rs) )
# , ('K-Nearest Neighbors' , KNeighborsClassifier() ) , ('K-Nearest Neighbors' , KNeighborsClassifier() )
# , ('LDA' , LinearDiscriminantAnalysis() ) , ('LDA' , LinearDiscriminantAnalysis() )
# , ('Logistic Regression' , LogisticRegression(**rs) ) , ('Logistic Regression' , LogisticRegression(**rs) )
# , ('Logistic RegressionCV' , LogisticRegressionCV(cv = 3, **rs)) , ('Logistic RegressionCV' , LogisticRegressionCV(cv = 3, **rs))
# , ('MLP' , MLPClassifier(max_iter = 500, **rs) ) , ('MLP' , MLPClassifier(max_iter = 500, **rs) )
# , ('Multinomial' , MultinomialNB() ) , ('Multinomial' , MultinomialNB() )
# , ('Naive Bayes' , BernoulliNB() ) , ('Naive Bayes' , BernoulliNB() )
# , ('Passive Aggresive' , PassiveAggressiveClassifier(**rs, **njobs) ) , ('Passive Aggresive' , PassiveAggressiveClassifier(**rs, **njobs) )
# , ('QDA' , QuadraticDiscriminantAnalysis() ) , ('QDA' , QuadraticDiscriminantAnalysis() )
# , ('Random Forest' , RandomForestClassifier(**rs, n_estimators = 1000, **njobs ) ) , ('Random Forest' , RandomForestClassifier(**rs, n_estimators = 1000, **njobs ) )
# , ('Random Forest2' , RandomForestClassifier(min_samples_leaf = 5 , ('Random Forest2' , RandomForestClassifier(min_samples_leaf = 5
# , n_estimators = 1000 , n_estimators = 1000
# , bootstrap = True , bootstrap = True
# , oob_score = True , oob_score = True
# , **njobs , **njobs
# , **rs , **rs
# , max_features = 'auto') ) , max_features = 'auto') )
# , ('Ridge Classifier' , RidgeClassifier(**rs) ) , ('Ridge Classifier' , RidgeClassifier(**rs) )
# , ('Ridge ClassifierCV' , RidgeClassifierCV(cv = 3) ) , ('Ridge ClassifierCV' , RidgeClassifierCV(cv = 3) )
# , ('SVC' , SVC(**rs) ) , ('SVC' , SVC(**rs) )
# , ('Stochastic GDescent' , SGDClassifier(**rs, **njobs) ) , ('Stochastic GDescent' , SGDClassifier(**rs, **njobs) )
# , ('XGBoost' , XGBClassifier(**rs, verbosity = 0, use_label_encoder = False, **njobs) ) , ('XGBoost' , XGBClassifier(**rs, verbosity = 0, use_label_encoder = False, **njobs) )
] ]
mm_skf_scoresD = {} mm_skf_scoresD = {}