Evaluation Methods for Machine Learning Classifiers

Explanation of Bias-Variance Analysis, Regularization, Performance Metrics, and an Implementation of Harmonic Classifier

Figure 1: A depiction of Results from a Bias-Variance Analysis (Source: Author)

In the previous articles, we have discussed various Machine Learning methods for classification tasks. We have also used terms like Regularization, Overfitting and Underfitting repeatedly. In this article, we shall go through these terms in detail and show how you can circumvent such problems. Furthermore, we shall also discuss various metrics for measuring the performance of a classifier.