目錄(80章)
倒序
- 封面
- 版權頁
- Credits
- About the Authors
- About the Reviewers
- www.PacktPub.com
- Support files eBooks discount offers and more
- 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 更新時間：2021-07-23 14:38:12
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