scikit-learn : Machine Learning Simplified

Chapter 4. Classifying Data with scikit-learn

This chapter will cover the following topics:

• Doing basic classifications with Decision Trees
• Tuning a Decision Tree model
• Using many Decisions Trees – random forests
• Tuning a random forest model
• Classifying data with support vector machines
• Generalizing with multiclass classification
• Using LDA for classification
• Working with QDA – a nonlinear LDA
• Using Stochastic Gradient Descent for classification
• Classifying documents with Naïve Bayes
• Label propagation with semi-supervised learning

Introduction

Classification can be very important in a lot of contexts. For example, if we want to automate some decision-making process, we can utilize classification. In cases where we need to investigate a fraud, there are so many ...