Category: Methods

Social Network Analysis in R, Social Network Analysis (SNA) is the process of exploring the social structure by using graph theory. It is mainly used for measuring and analyzing the structural properties of the...

Cluster Analysis in R, when we do data analytics, there are two kinds of approaches one is supervised and another is unsupervised. Clustering is a method for finding subgroups of observations within a data...

Gradient Boosting in R, in this tutorial we are going to discuss extreme gradient boosting. Why is eXtreme Gradient Boosting in R? Popular in machine learning challenges. Fast and accurate Can handle missing values....

Market Basket Analysis in R, Market Basket Analysis is very popular. In this tutorial, the main idea is to identify the purchase pattern of the products, “what goes with what”. Based on this information...

Basic Functions in R, in this tutorial, we are going to discuss basic statistical or user-defined functions. Functions are very useful in R for faster and safe execution. Some will be inbuilt functions and...

Random Forest in R, Random forest developed by an aggregating tree and this can be used for classification and regression. One of the major advantages is its avoids overfitting. The random forest can deal...

Linear optimization using R, in this tutorial we are going to discuss the linear optimization problems in R. Optimization is everything nowadays. We all have finite resources and time and we want to make...

LSTM network in R, Recurrent Neural Networks will be discussed in this tutorial. Recurrent Neural Networks are extremely useful for resolving problems involving sequences of numbers. The major applications involved in the sequence of...

Deep Neural Network in R, Neural Network is just like a human nervous system, which is made up of interconnected neurons, in other words, a neural network is made up of interconnected information processing...