## Step by Step Tutorial on Decision Tree using Python

In this blog, the aim is to show you steps of building a Decision Tree using Python Jupiter Notebook. If you are interested to learn Decision Tree algorithm, we have an excellent tutorial on "Decision Tree Algorithm - CART". We are using the same data for explaining the steps involved in building a decision tree. ... Read more

## Decision Tree CART Algorithm Part 3

In the precious blogs, we have explained on selecting Best Split for each of the independent variables. Now we need to select the best variable, again consideration is Gini Index Value. For each of the independent Variables, we have best split and its Gini Index value. Here is the table. Variable Spend in the last ... Read more

## CART Algorithm: Best Split for a Categorical Variable

Similar to continuous variables, Decision Tree Algorithm - CART has to find the best split for categorical variable as well. Only difference will be to find possible cut off values. For example, we have a variable - education- it had 4 levels -"University","Graduate","High School" and "Others". We consider all possible two way splits for the ... Read more

## CART Algorithm for Decision Tree

Classification and Regression Tree (CART) is one of commonly used Decision Tree algorithms. In this post, we will explained the steps of CART algorithm using an example data. Decision Tree is a recursive partitioning approach and CART split each of the input node into two child nodes, so CART decision tree is Binary Decision Tree. ... Read more

## Decision Tree- Credit Risk Data and Model

Decision Tree is one of the commonly used exploratory data analysis and objective segmentation techniques. Great advantage with Decision Tree is that the its output is relatively easy to understand or intrepret. Introduction to Decision Tree and intrepet Decision Tree results Simple way to understand decision tree is that it is hierarchical approach to partition ... Read more

## Random Forest Using R: Step by Step Tutorial

Random Forest: Overview Random Forest is an ensemble learning  (both classification and regression) technique. It is one of the commonly used predictive modelling and machine learning technique. Before understanding random forest algorithm, it is recommended to understand about decision tree algorithm & applications. A non-technical description of decision tree. A simple explanation of why is it ... Read more

## Decision Tree: Entropy and Information Gain

A decision tree is a hierarchical or tree like representation of decisions. Decision Tree is a technique to iteratively break input data (or node) into two or more data samples (or nodes). And this recursive partitioning of input data (or node) continue until it meets specified condition(s). How decision tree is built? There are different ... Read more

## CART Decision Tree: Gini Index Explained

Different algorithms and impurity measures are used for building a Decision Tree (Decision Tree – A Statistical and Analytical tools of better Decisions). One of the decision tree algorithms is CART (Classification and Regression Tree). CART is developed by Breiman, Friedman, Olshen, & Stone in 1984 (Book - Classification and Regression Trees). Classification Tree: When ... Read more

## GINI Index: Work out Example

CART is one of the decision tree algorithms and it uses GINI index based impurity measure. A detailed explanation on CART algorithm - CART Decision Tree: Gini Index Explained Binary Target Variable: Worked out Example Consider an example where target variable is binary, the summary table for such example will be similar to below table.   ... Read more

## Decision Tree: A statistical and analytical tool for effective decisions

A decision tree is a hierarchical or tree like representation of decisions. Decision Tree is a technique to iteratively break input data (or node) into two or more data samples (or nodes).  And this recursive partitioning of input data (or node) continue until it meets specified condition(s). Decision Tree is a method for objective segmentation. ... Read more

## Predict and Analyze results of CART Decision Tree

Initial steps to build a Decision Tree is explained and illustrated in our previous blog- Decision Tree using rpart in R. The steps covered in previous blogs Load Libraries - rpart and rpart.plot Read input data and split into development and validation samples Build Decision Tree Plot Decision Tree Also a few blogs are written on What is Decision ... Read more

## Decision Tree using rpart in R

Decision Tree is one of the commonly used exploratory data analysis and objective segmentation techniques. Great advantage with Decision Tree is that the its output is relatively easy to understand or intrepret. Introduction to Decision Tree and intrepet Decision Tree results Simple way to understand decision tree is that it is hierarchical approach to partition ... Read more

## Segmentation-a-perspective

Segmentation is one of the old concepts being used across fields and by non-technical people. People are segmentation at least into two groups “Male” and “Female” based on gender characteristics. Now let’s try to understand these two segments better. These two segments will be very different on a few characteristics (that are variables in analytics ... Read more

## Segmentation - A Perspective

Segmentation is one of the old concepts being used across fields and by non-technical people. People are segmented at least into two groups “Male” and “Female” based on gender characteristics.  Now let’s try to understand these two segments better.  These two segments will be very different on a few characteristics (that are variables in analytics ... Read more