Ensemble Technique - Random Forest in R

Machine Learning Techniques - I

Machine Learning is a buzz word these days in the world of data science and analytics. R and Python have gone popular as these tools are full of advanced machine learning techniques.

@ Ask Analytics we have covered many basic machine learning techniques so far, now we are starting with advanced techniques!

The concepts of Bagging and Boosting

Ensemble Learning Techniques

In one of the previous posts we covered Random Forest, one of the most popular ensemble learning techniques. We covered concepts of bagging and boosting there, but not much in depth. Let's now understand the concepts of ensemble learning in greater details.

Decision Tree With Party Package

Decision Science

I still remember those olden golden days, when we did not have many options for anything, be it Biscuits or the Decision Tree. Generally people used to buy Parle-G biscuits in India and used to draw decision tree with SAS or SPSS.

These days market is full of assortment, which is both bad and good. Bad because people often get confused with too many choices, good because you don't have to compromise with lack of options. Data science has got evolved much with assortment availability. R itself provides you many packages to do the same work. Let's learn the beautiful party package for building decision tree and enjoy the power of assortment! Read it and you would understand the significance of its name.

Decision Tree in R with {tree} Package

Decision Science

We earlier covered the decision tree in R using {rpart} package in one of our previous articles. In R there are many packages that can be used for making a decision tree, out of which {tree} and {party} are my hot favorites. I will cover both of the packages one by one @ Ask Analytics.

Let's first learn usage of {tree} !

Decision Tree in R - A Telecom Case Study

How to draw a Decision Tree in R

This article has been written in continuation of one of the previous articles covering :
1. What is Entropy ?
2. What is Information Gain?

We had explored how Decision Tree assigns variables on the basis of  Information Gain. Now we will learn how to draw a decision tree in R on a telecom industry example and would understand the behind scene algorithm once again.

Ready ... Steady ... Go !

How to decide root node variable in decision tree

Untangle the puzzles of Decision Science

While I was learning "How to make a Decision Tree in SAS" I was curious about : "On what basis does SAS recommend variable next in the hierarchical structure?"

The question made me to delve deeper into it, to identify behind the screen chemistry … It took me several months to understand the complex mathematics (as had to take multiple naps in between).

Do you have the same question in your mind ? No problem, I will tell you the same with a "No sleeping" guarantee !