Implementing Parallel Processing in 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

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...
How to Perform Hierarchical Clustering using R

How to Perform Hierarchical Clustering using R

What is Hierarchical Clustering? Clustering is a technique to club similar data points into one group and separate out dissimilar observations into different groups or clusters. In Hierarchical Clustering, clusters are created such that they have a predetermined...

How to implement Random Forests in R

Imagine you were to buy a car, would you just go to a store and buy the first one that you see? No, right? You usually consult few people around you, take their opinion, add your research to it and then go for the final decision. Let’s take a simpler scenario:...

Understanding Naïve Bayes Classifier Using R

The Best Algorithms are the Simplest The field of data science has progressed from simple linear regression models to complex ensembling techniques but the most preferred models are still the simplest and most interpretable. Among them are regression, logistic, trees...