Logistic Regression, Machine Learning, Predictive Analytics, Data Science, Classification.
dataset, we use ‘liblinear’ as a solver. C parameter indicates inverse of regularization strength which must be a positive float. Smaller values specify stronger regularization. logistic_model = LogisticRegression(C=0.20,solver='liblinear') logistic_model.fit(X_train,y_train) Now We can predict