X_Classifier.predict_proba returns array of shape (n_samples, 1) instead of (n_samples, 2). #125
Description
Description of Issue:
predict_proba method implemented in scikit-learn Estimators and LGBM usually returns returns the predicted probability for each class for each sample. XClassifier deviates from this behaviour returning only probabilities estimates for class 1.
How to reproduce:
from xplainable.core.models import XClassifier
from sklearn.datasets import make_classification
import numpy as np
X, y = make_classification(n_samples=1000,n_features=4,random_state=42,n_classes=2)
X = pd.DataFrame(X,columns=['Feat_'+str(i) for i in range(4)])
y = pd.Series(y)
print(f'Shape of training data {X.shape}')
print(f'Shape of target {y.shape}')
x_model = XClassifier()
x_model.fit(X, y)
print(x_model.predict_proba(X).shape)
Screenshot
