封面
版权页
Credits
About the Authors
About the Reviewers
www.PacktPub.com
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Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Chapter 1. Getting Started with R
Reading data from different sources
Reading data from a database
Data types in R
Data preprocessing techniques
Performing data operations
Control structures in R
Bringing data to a usable format
Summary
Chapter 2. Exploratory Data Analysis
The Titanic dataset
Descriptive statistics
Inferential statistics
Univariate analysis
Bivariate analysis
Multivariate analysis
Summary
Chapter 3. Pattern Discovery
Transactional datasets
Apriori analysis
Support confidence and lift
Generating filtering rules
Plotting
Sequential dataset
Apriori sequence analysis
Understanding the results
Business cases
Summary
Chapter 4. Segmentation Using Clustering
Datasets
Centroid-based clustering and an ideal number of clusters
Implementation using K-means
Visualizing the clusters
Connectivity-based clustering
Visualizing the connectivity
Business use cases
Summary
Chapter 5. Developing Regression Models
Datasets
Sampling the dataset
Logistic regression
Evaluating logistic regression
Linear regression
Evaluating linear regression
Methods to improve the accuracy
Ensemble models
Summary
Chapter 6. Time Series Forecasting
Datasets
Extracting patterns
Forecasting using ARIMA
Forecasting using Holt-Winters
Methods to improve accuracy
Summary
Chapter 7. Recommendation Engine
Dataset and transformation
Recommendations using user-based CF
Recommendations using item-based CF
Challenges and enhancements
Summary
Chapter 8. Communicating Data Analysis
Dataset
Plotting using the googleVis package
Creating an interactive dashboard using Shiny
Summary
Index
更新时间：2021-07-23 14:38:12
完结共80章
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