Regression refers to predictive modeling problems that involve predicting a numeric value. — It is different from the classification that involves predicting a class label. Unlike classification, you cannot use classification accuracy to evaluate the predictions made by a regression model. I have wrote article on evaluation metrics for classification task you can checkout here . Instead, you must use error metrics specifically…

A classifier is only as good as the metric used to evaluate it. Evaluating a model is a major part of building an effective machine learning model. The most frequent classification evaluation metric that we use should be ‘Accuracy’. You might believe that the model is good when the accuracy…

Neural network activation functions are a crucial component of deep learning. Activation functions determine the output of a deep learning model, its accuracy, and also the computational efficiency of training a model — which can make or break a large-scale neural network. …