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modified ml params and models

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Tanushree Tunstall 2022-05-19 02:35:50 +01:00
parent 3ed7840f60
commit 4dbc90ad44
6 changed files with 17 additions and 332 deletions
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11
MultClassPipe3.py
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@ -27,7 +27,7 @@ from sklearn.compose import ColumnTransformer
from sklearn.compose import make_column_transformer
from sklearn.metrics import confusion_matrix, accuracy_score, precision_score, recall_score
from sklearn.metrics import roc_auc_score, roc_curve, f1_score, matthews_corrcoef
from sklearn.metrics import roc_auc_score, roc_curve, f1_score, matthews_corrcoef, jaccard_score
from sklearn.metrics import make_scorer
from sklearn.metrics import classification_report
@ -70,7 +70,7 @@ scoring_fn = ({ 'fscore' : make_scorer(f1_score)
, 'recall' : make_scorer(recall_score)
, 'accuracy' : make_scorer(accuracy_score)
, 'roc_auc' : make_scorer(roc_auc_score)
#, 'jaccard' : make_scorer(jaccard_score)
, 'jaccard' : make_scorer(jaccard_score)
})
@ -122,10 +122,11 @@ def MultClassPipeSKFCV(input_df, target, skf_cv, var_type = ['numerical', 'categ
mlp = MLPClassifier(max_iter = 500, **rs)
dt = DecisionTreeClassifier(**rs)
et = ExtraTreesClassifier(**rs)
rf = RandomForestClassifier(**rs)
rf = RandomForestClassifier(**rs,
n_estimators = 1000 )
rf2 = RandomForestClassifier(
min_samples_leaf = 50
, n_estimators = 150
min_samples_leaf = 5
, n_estimators = 1000
, bootstrap = True
, oob_score = True
, **njobs