A Solution to Missing Data: Imputation Using R

A Solution to Missing Data: Imputation Using R

by | Aug 6, 2018 | Analytics, R

Handling missing values is one of the worst nightmares a data analyst dreams of. In situations, a wise analyst ‘imputes’ the missing values instead of dropping them from the data. Missing Data in Analysis At times while working on data, one may come across missing...
Learn Generalized Linear Models (GLM) using R

Learn Generalized Linear Models (GLM) using R

by | Aug 5, 2018 | Analytics, R

In this article, we aim to discuss various GLMs that are widely used in the industry. We focus on: a) log-linear regression b) interpreting log-transformations and c) binary logistic regression. Editor’s note: Data files discussed below can be acquired here:...
Machine Learning Using Support Vector Machines

Machine Learning Using Support Vector Machines

by | Aug 4, 2018 | Analytics, R

Support Vector Machines (SVM) is a data classification method that separates data using hyperplanes. The concept of SVM is very intuitive and easily understandable. If we have labeled data, SVM can be used to generate multiple separating hyperplanes such that the data...

Implementing Parallel Processing in R

by | Aug 3, 2018 | Analytics, R

If something takes less time if done through parallel processing, why not do it and save time? Modern laptops and PCs today have multi core processors with sufficient amount of memory available and one can use it to generate outputs quickly. Parallelizing your codes...
Exploring Assumptions of K-means Clustering using R

Exploring Assumptions of K-means Clustering using R

by | Aug 2, 2018 | Analytics, R

K-Means Clustering is a well known technique based on unsupervised learning. As the name mentions, it forms ‘K’ clusters over the data using mean of the data. Unsupervised algorithms are a class of algorithms one should tread on carefully. Using the wrong algorithm...