November 29, 2019 Principal Components Analysis (PCA) – Better Explained Principal Components Analysis (PCA) is an algorithm to transform the columns of a dataset into a new set of features called Principal Components. By…

June 7, 2018 Feature Selection – Ten Effective Techniques with Examples In machine learning, Feature selection is the process of choosing variables that are useful in predicting the response (Y). It is considered a good…

March 11, 2018 Caret Package – A Practical Guide to Machine Learning in R Caret Package is a comprehensive framework for building machine learning models in R. In this tutorial, I explain nearly all the core features of…

September 30, 2017 Top 15 Evaluation Metrics for Classification Models Choosing the right evaluation metric for classification models is important to the success of a machine learning app. Monitoring only the ‘accuracy score’ gives…

September 13, 2017 Logistic Regression – A Complete Tutorial With Examples in R Logistic regression is a predictive modelling algorithm that is used when the Y variable is binary categorical. That is, it can take only two…

March 12, 2017 Complete Introduction to Linear Regression in R Linear regression is used to predict the value of a continuous variable Y based on one or more input predictor variables X. The aim…