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Applied Predictive Modeling

Overview of attention for book
Cover of 'Applied Predictive Modeling'

Table of Contents

  1. Altmetric Badge
    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 A Short Tour of the Predictive Modeling Process
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    Chapter 3 Data Pre-processing
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    Chapter 4 Over-Fitting and Model Tuning
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    Chapter 5 Measuring Performance in Regression Models
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    Chapter 6 Linear Regression and Its Cousins
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    Chapter 7 Nonlinear Regression Models
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    Chapter 8 Regression Trees and Rule-Based Models
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    Chapter 9 A Summary of Solubility Models
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    Chapter 10 Case Study: Compressive Strength of Concrete Mixtures
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    Chapter 11 Measuring Performance in Classification Models
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    Chapter 12 Discriminant Analysis and Other Linear Classification Models
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    Chapter 13 Nonlinear Classification Models
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    Chapter 14 Classification Trees and Rule-Based Models
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    Chapter 15 A Summary of Grant Application Models
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    Chapter 16 Remedies for Severe Class Imbalance
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    Chapter 17 Case Study: Job Scheduling
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    Chapter 18 Measuring Predictor Importance
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    Chapter 19 An Introduction to Feature Selection
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    Chapter 20 Factors That Can Affect Model Performance
Attention for Chapter 13: Nonlinear Classification Models
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Citations

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Chapter title
Nonlinear Classification Models
Chapter number 13
Book title
Applied Predictive Modeling
Published by
Springer New York, January 2013
DOI 10.1007/978-1-4614-6849-3_13
Book ISBNs
978-1-4614-6848-6, 978-1-4614-6849-3
Authors

Max Kuhn, Kjell Johnson

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 24%
Student > Ph. D. Student 6 24%
Student > Master 5 20%
Student > Doctoral Student 2 8%
Other 2 8%
Other 2 8%
Unknown 2 8%
Readers by discipline Count As %
Computer Science 5 20%
Agricultural and Biological Sciences 3 12%
Engineering 3 12%
Medicine and Dentistry 2 8%
Neuroscience 2 8%
Other 4 16%
Unknown 6 24%

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