Decision Trees
Introduction
In previous section, we studied about Model Selection : Logistic Regression
Decision tree is a type of supervised learning algorithm that is mostly used in classification problems.In this technique, we split the population or sample into two or more homogeneous sets based on most significant differentiation in input variables.
Contents
- What is segmentation
- What is a Decision tree
- Decision Trees Algorithm
- Best Splitting attribute
- Building decision Trees
- Tree validation
- Pruning
- Prediction using the model
What is Segmentation?
- Imagine a scenario where we want to run a SMS marketing campaign to attract more customers in the next quarter
- Some customers like to see high discount
- Some customers want to see a large collection of items
- Some customers are fans of particular brands
- Some customers are Male some are Female
- Divide them based on their demographics, buying patterns and profile related attributes
- One size doesn’t fit all
- Divide the population in such a way that
- Customers inside a group are homogeneous
- Customers across groups are heterogeneous
- Is there any statistical way of dividing them correctly based on the data
Segmentation Business Problem
The Data
Re-Arranging the data
The next post is about the Decision Tree approach.
