Chapter 3. Predictive Modeling
In this chapter, we will cover the following recipes:
- Building a linear classifier using Support Vector Machines (SVMs)
- Building a nonlinear classifier using SVMs
- Tackling class imbalance
- Extracting confidence measurements
- Finding optimal hyperparameters
- Building an event predictor
- Estimating traffic
Introduction
Predictive modeling is probably one of the most exciting fields in data analytics. It has gained a lot of attention in recent years due to massive amounts of data being available in many different verticals. It is very commonly used in areas concerning data mining to forecast future trends.
Predictive modeling is an analysis technique that is used to predict the future behavior of a system. It is a collection of ...
Get Python Machine Learning Cookbook now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
