By the end of this tutorial on forcats package for working with factors in R, you will be able to change the order of levels, inspect levels, change the values of levels, combine levels, and add/drop levels more efficiently.

Binary Logistic Regression is used to explain the relationship between the categorical dependent variable and one or more independent variables. When the dependent variable is dichotomous, we use binary logistic regression. However, by default, a binary logistic regression is almost always called logistics regression. Overview – Binary Logistic Regression The logistic ...

In this tutorial on purrr package in R, you will learn how to use functions from the purrr package in R to improve the quality of your code and understand the advantages of purrr functions compared to equivalent base R functions.

In this tutorial, learn how k-means clustering algorithm works along with the example code in R.

In this section, we will learn how to execute Ridge Regression in R. We use ridge regression to tackle the multicollinearity problem. Due to multicollinearity, the model estimates (least square) see a large variance. Ridge regression is a method by which we add a degree of bias to the regression ...

LASSO regression stands for Least Absolute Shrinkage and Selection Operator. The algorithm is another variation of linear regression, just like ridge regression. We use lasso regression when we have a large number of predictor variables. Overview – Lasso Regression Lasso regression is a parsimonious model that performs L1 regularization. The L1 ...

The ggplot2 package in R provides a reliable system for describing and building graphs. The package is capable of creating elegant and aesthetically pleasing graphics.