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Updated 3 years ago
Decision Trees on titanic dataset
Table of Contents
- Problem Statement
- Data Loading and Description
- Preprocessing
- Decision Tree
- 4.1 Introduction of Decision Tree
- 4.2 Important Terminology related to Decision Trees
- 4.3 Types of Decision Trees
- 4.4 Concept of Homogenity
- 4.5 How does a tree decide where to split?
- 4.5.1 Gini Index
- 4.5.2 Information Gain
- 4.5.1 Gini Index
- 4.6 Advantages of using Decision Tree
- 4.7 Shortcomings of Decision Trees
- 4.8 Preparing X and y using pandas
- 4.9 Splitting X and y into training and test datasets.
- 4.10 Decision Tree in scikit-learn
- 4.11 Using the Model for Prediction
- 4.1 Introduction of Decision Tree
- Model evaluation
- Decision Tree with Gridsearch
1. Problem Statement
The goal is to predict survival of passengers travelling in RMS Titanic using Logistic regression.