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Applied predictive modeling / Max Kuhn, Kjell Johnson.

By: Kuhn, Max.
Contributor(s): Johnson, Kjell.
Publisher: New York : Springer, 2013Description: xiii, 600 pages : illustrations (some color) ; 24 cm.Content type: text Media type: unmediated Carrier type: volumeISBN: 1461468485; 9781461468486.Subject(s): Mathematical statistics | Mathematical models | Prediction theory | Mathematical models | Mathematical statistics | Prediction theory | Vorhersagetheorie | Mathematisches ModellLOC classification: QA276 | .K84 2013
Contents:
General Strategies. A Short Tour of the Predictive Modeling Process -- Data Pre-processing -- Over-Fitting and Model Tuning -- Regression Models. Measuring Performance in Regression Models -- Linear Regression and Its Cousins -- Nonlinear Regression Models -- Regression Trees and Rule-Based Models -- A Summary of Solubility Models -- Case Study: Compressive Strength of Concrete Mixtures -- Classification Models. Measuring Performance in Classification Models -- Discriminant Analysis and Other Linear Classification Models -- Nonlinear Classification Models -- Classification Trees and Rule-Based Models -- A Summary of Grant Application Models -- Remedies for Severe Class Imbalance -- Case Study: Job Scheduling -- Other Considerations. Measuring Predictor Importance -- An Introduction to Feature Selection -- Factors That Can Affect Model Performance.
List(s) this item appears in: Data Analysis
Item type Current location Call number Status Date due Barcode Item holds
BOOK BOOK NCAR Library
Mesa Lab
QA276 .K84 2013 Available 50583020002766
Total holds: 0

Includes bibliographical references and indexes.

General Strategies. A Short Tour of the Predictive Modeling Process -- Data Pre-processing -- Over-Fitting and Model Tuning -- Regression Models. Measuring Performance in Regression Models -- Linear Regression and Its Cousins -- Nonlinear Regression Models -- Regression Trees and Rule-Based Models -- A Summary of Solubility Models -- Case Study: Compressive Strength of Concrete Mixtures -- Classification Models. Measuring Performance in Classification Models -- Discriminant Analysis and Other Linear Classification Models -- Nonlinear Classification Models -- Classification Trees and Rule-Based Models -- A Summary of Grant Application Models -- Remedies for Severe Class Imbalance -- Case Study: Job Scheduling -- Other Considerations. Measuring Predictor Importance -- An Introduction to Feature Selection -- Factors That Can Affect Model Performance.

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