Summary

Predictive modeling uses statistics in order to predict outcomes. However, predictive modeling can be applied to events regardless of time of occurrence. When it comes to the applications of predictive modeling, techniques are used in various fields including algorithmic trading, uplift modeling, archaeology, health care, customer relationship management, and many others. This book covers the predictive modeling process with fundamental steps of the process, data preprocessing, data splitting and crucial steps of model tuning and improving model performance.
Further, the book will introduce you to the most common classification and regression techniques including logistic regression which is widely used when it comes to the finding the probability of event success or event failure. You will get to know the common predictive modeling techniques as well such as stepwise regression, polynomial regression, and ridge regression which will help you when you are dealing with the data that suffers from very common multicollinearity where independent variables are highly correlated.
What you will learn in Applied Predictive Modeling:


Most common predictive modeling techniques
Types of regression models
The overall predictive modeling process
Fundamental steps to effective and highly accurate predictive modeling
How to build predictive model with logistic regression with code listings
How to build predictive model using Python
How to enhance your model performance
Parameters for increasing the overall predictive power
How to handle class imbalance
Common causes of poor model performance

Listen to this book now and learn more about applied predictive modeling!
©2017 Steven Taylor (P)2017 Steven Taylor
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Customer Reviews

Most Helpful
5 out of 5 stars
By lAYANA on 26-03-18

NICE BOOK TO HAVE

Very nice book with lots of useful information and enough case studies and learning materials. Best book.

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4 out of 5 stars
By sana on 26-03-18

Good

The book is very well categorized into several sections and each section contains chapters related to various aspects of Applied Predictive.

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Customer Reviews

Most Helpful
5 out of 5 stars
By shifana on 23-11-17

5/5 great Grab..

The book will introduce you to the most common classification and regression techniques including logistic regression which is widely used when it comes to the finding the probability of event success or event failure..
Highly suggest It...

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5 out of 5 stars
By catherine on 23-11-17

I found it so informative..

The author describes the science behind the models and includes some problems involved in using these models as well as some methods for overcoming them.

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