Blog Archives

Dealing with The Problem of Multicollinearity in R

August 15, 2018
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Dealing with The Problem of Multicollinearity in R

Imagine a situation where you are asked to predict the tourism revenue for a country, lets say India. In this case, your output or dependent or response variable will be total revenue earned (in USD) in a given year. But, what about independent or predictor variables? You have been provided with two sets of predictor Continue reading Dealing...

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Anomaly Detection in R

June 11, 2018
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Anomaly Detection in R

The World of Anomalies Imagine you are a credit card selling company and you know about a particular customer who makes a purchase of 25$ every week. You guessed this purchase is his fixed weekly rations but one day, this customer makes a different purchase of 700$. This development will not just startle you but … Continue reading Anomaly...

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Exploratory Factor Analysis in R

May 10, 2018
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Exploratory Factor Analysis in R

Changing Your Viewpoint for Factors In real life, data tends to follow some patterns but the reasons are not apparent right from the start of the data analysis. Taking a common example of a demographics based survey, many people will answer questions in a particular ‘way’. For example, all married men will have higher expenses … Continue reading Exploratory...

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Discriminant Analysis: Statistics All The Way

March 27, 2018
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Discriminant Analysis: Statistics All The Way

Discriminant analysis is used when the variable to be predicted is categorical in nature. This analysis requires that the way to define data points to the respective categories is known which makes it different from cluster analysis where the classification criteria is not know. It works by calculating a score based on all the predictor Continue reading Discriminant...

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Steps to Perform Survival Analysis in R

March 26, 2018
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Steps to Perform Survival Analysis in R

Another way of analysis? When there are so many tools and techniques of prediction modelling, why do we have another field known as survival analysis? As one of the most popular branch of statistics, Survival analysis is a way of prediction at various points in time. This is to say, while other prediction models make Continue reading Steps...

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Whys and Hows of Apply Family of Functions in R

February 22, 2018
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Introduction to Looping system Imagine you were to perform a simple task, lets say calculating sum of columns for 3X3 matrix, what do you think is the best way? Calculating it directly using traditional methods such as calculator or even pen and paper doesnt sound like a bad approach. A lot of us may prefer Continue reading Whys...

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Understanding Nave Bayes Classifier Using R

January 22, 2018
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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 and naive bayes techniques. Naive Bayes algorithm, in particular is a logic based technique which Continue reading Understanding...

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How to implement Random Forests in R

January 9, 2018
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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. Lets take a simpler scenario: whenever you go for Continue reading How...

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How to Perform Hierarchical Clustering using R

December 18, 2017
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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 ordering i.e. a hierarchy. For example, consider the concept hierarchy of a library. A library has many Continue reading How...

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Exploring Assumptions of K-means Clustering using R

August 7, 2017
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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 will give completely botched up results and all the effort will go Continue reading Exploring...

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