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Applied Predictive Modeling
other
Author(s):
Max Kuhn
,
Kjell Johnson
Publication date
(Print):
2013
Publisher:
Springer New York
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New directions in predictive processing
Author and book information
Book
ISBN (Print):
978-1-4614-6848-6
ISBN (Electronic):
978-1-4614-6849-3
Publication date (Print):
2013
DOI:
10.1007/978-1-4614-6849-3
SO-VID:
36e65256-68c3-4f65-806a-5effe10ab0e5
License:
http://www.springer.com/tdm
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Book chapters
pp. 1
Introduction
pp. 19
A Short Tour of the Predictive Modeling Process
pp. 27
Data Pre-processing
pp. 61
Over-Fitting and Model Tuning
pp. 95
Measuring Performance in Regression Models
pp. 101
Linear Regression and Its Cousins
pp. 141
Nonlinear Regression Models
pp. 173
Regression Trees and Rule-Based Models
pp. 221
A Summary of Solubility Models
pp. 225
Case Study: Compressive Strength of Concrete Mixtures
pp. 247
Measuring Performance in Classification Models
pp. 275
Discriminant Analysis and Other Linear Classification Models
pp. 329
Nonlinear Classification Models
pp. 369
Classification Trees and Rule-Based Models
pp. 415
A Summary of Grant Application Models
pp. 419
Remedies for Severe Class Imbalance
pp. 445
Case Study: Job Scheduling
pp. 463
Measuring Predictor Importance
pp. 487
An Introduction to Feature Selection
pp. 521
Factors That Can Affect Model Performance
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