At beginning problem was that class were umbalced and I balanced.
Balancement works for f1 score in svc  , but none improvment from f1 score of neural netowrk, it also reduce the accuracy! why? . I also tried Kfold and crossfold validation, same result. Also tried to semplify level, but nothing.
scaling:
`
X_ = dataset_train_upsampled.drop([‘LABEL’], axis=1)
y_ = dataset_train_upsampled[‘LABEL’]
X_=np.array(X_)
y_=np.array(y_)
X_train_full_, X_test_, y_train_full_, y_test_ = train_test_split(X_, y_,test_size=0.2, random_state=42)
X_train_, X_validation_, y_train_, y_validation_ = train_test_split(X_train_full_, y_train_full_, random_state=42)
scaler = StandardScaler()
X_train_ = scaler.fit_transform(X_train_)
X_validation_ = scaler.transform(X_validation_)
X_test_ = scaler.transform(X_test_)
`

reteneurale1479×663 47 KB