I have a feature vector table which looks like this-
This a table with 156 columns or features.I want to apply feature selection algorithm to this before applyinh my classification model.
This is what I am using-
dataset = pd.read_csv('.csv') X = dataset.iloc[:, 1:157].values y = dataset.iloc[:,0].values ##normalize scaler = MinMaxScaler() scaler.fit(X) MinMaxScaler(copy=True, feature_range=(0, 1)) X_normalized = scaler.transform(X) ##feature selection sel = SelectKBest(chi2, k='all') sel.fit_transform(X_normalized, y) print(sel.scores_)
this is the result of
print(sel.scores_) I am getting-
As can be seen they are not all between 0 and 1.
I a referring this research paper as my source-