TY  - BOOK
AU  - Nisbet, Robert
TI  - Handbook of statistical analysis and data mining applications
SN  - 9780124166325
PY  - 2018///
PB  - Elsevier
KW  - Data mining--Statistical methods
N1  - Chapter 1 - The Background for Data Mining Practice

Chapter 2 - Theoretical Considerations for Data Mining

Chapter 3 - The Data Mining and Predictive Analytic Process

Chapter 4 - Data Understanding and Preparation

Chapter 5 - Feature Selection

Chapter 6 - Accessory Tools for Doing Data Mining

Chapter 7 - Basic Algorithms for Data Mining: A Brief Overview

Chapter 8 - Advanced Algorithms for Data Mining

Chapter 9 - Classification

Chapter 10 - Numerical Prediction

Chapter 11 - Model Evaluation and Enhancement

Chapter 12 - Predictive Analytics for Population Health and Care

Chapter 13 - Big Data in Education: New Efficiencies for Recruitment, Learning, and Retention of Students and Donors

Chapter 14 - Customer Response Modeling

Chapter 15 - Fraud Detection

Chapter 16 - The Apparent Paradox of Complexity in Ensemble Modeling

Chapter 17 - The “Right Model” for the “Right Purpose”: When Less Is Good Enough

Chapter 18 - A Data Preparation Cookbook

Chapter 19 - Deep Learning

Chapter 20 - Significance versus Luck in the Age of Mining: The Issues of P-Value “Significance” and “Ways to Test Significance of Our Predictive Analytic Models”

UR  - https://www.sciencedirect.com/science/book/9780124166325
ER  -