Machine Learning or Deep Learning model must be in balanced state

Machine Learning or Deep Learning model must be in balanced state

Machine Learning or Deep Learning model must be in balanced state   If you ever built a supervised Machine Learning model on some real-time data, it is impossible that it will perform well both on train set and test set in a first evaluation attempt. Real-time data is so noisy, of course as part of model building activity you might have performed enough cleanup and did efficient feature engineering, though usually the model either will tend to overfit or underfit the training data.   How do you detect if the model is underfit (Bias Problem) or overfit (Variance Problem)? Usually…