R: Unleash Machine Learning Techniques

R: Unleash Machine Learning Techniques
by 作者: Brett Lantz,Cory Lesmeister,Dipanjan Sarkar,Raghav Bali
Pages: 1123 pages
Edition 版本: 1
Language 语言: English
Publisher Finelybook 出版社: Packt Publishing
Publisher Finelybook 出版日期: 2016-10-24
ISBN-10 书号: B01MQ4M4VO
ISBN-13 书号: 9781787127340
Contents
Module 1: R Machine Learning By Example
Chapter 1: Getting Started with R and Machine Learning
Chapter 2: Let's Help Machines Learn
Chapter 3: Predicting Customer Shopping Trends with Market Basket Analysis
Chapter 4: Building a Product Recommendation System
Chapter 5: Credit Risk Detection and Prediction – Descriptive Analytics
Chapter 6: Credit Risk Detection and Prediction – Predictive Analytics
Chapter 7: Social Media Analysis – Analyzing Twitter Data
Chapter 8: Sentiment Analysis of Twitter Data
Module 2: Machine Learning with R
Chapter 1: Introducing Machine Learning
Chapter 2: Managing and Understanding Data
Chapter 3: Lazy Learning – Classification Using Nearest Neighbors
Chapter 4: Probabilistic Learning – Classification Using Naive Bayes
Chapter 5: Divide and Conquer – Classification Using Decision Trees and Rules
Chapter 6: Forecasting Numeric Data – Regression Methods
Chapter 7: Black Box Methods – Neural Networks and Support Vector Machines
Chapter 8: Finding Patterns – Market Basket Analysis Using Association Rules
Chapter 9: Finding Groups of Data – Clustering with k-means
Chapter 10: Evaluating Model Performance
Chapter 11: Improving Model Performance
Chapter 12: Specialized Machine Learning Topics
Module 3: Mastering Machine Learning with R
Chapter 1: A Process for Success
Chapter 2: Linear Regression – The Blocking and Tackling of Machine Learning
Chapter 3: Logistic Regression and Discriminant Analysis
Chapter 4: Advanced Feature Selection in Linear Models
Chapter 5: More Classification Techniques – K-Nearest Neighbors and Support Vector Machines
Chapter 6: Classification and Regression Trees
Chapter 7: Neural Networks
Chapter 8: Cluster Analysis
Chapter 9: Principal Components Analysis
Chapter 10: Market Basket Analysis and Recommendation Engines
Chapter 11: Time Series and Causality
Chapter 12: Text Mining
Appendix: R Fundamentals