R Data Mining

Key Features

• Understand the basics of data mining and why R is a perfect tool for it.
• Manipulate your data using the popular R packages and gather valuable business insights from it.
• Written in a clear, easy to understand manner, and includes lots of practical examples involving real-world datasets

Book Description

R is widely used in leveraging data mining techniques across many different industries, including finance, medicine, scientific research and more. This book will empower you to produce and show impressive analyses from the data, selecting and implementing the appropriate data mining techniques in R.

The book begins with a detailed introduction to data mining and why R is a popular alternative for it. You will get a comprehensive coverage of the various R packages which you can use in the data mining process. We will then proceed to use these packages for manipulating various datasets, through practical examples including real-world datasets. Implement algorithms like k-means, SVM, and more, and techniques like classification and cluster analysis to extract insightful patterns and associations. Topics like outlier detection, regression analysis, anomaly detection and network analysis are also covered, in a very easy to understand manner. You will also use the popular ggplot2 package to visualize the insights you get from the analysis, and aid your decision-making.

By the end of this book, you will have grasped the fundamentals of data mining, and the various techniques you can deploy with the popular R packages to get the most out of your data.

What you will learn

• Get introduced to most relevant packages for data mining within the R environment.
• Get confident about data quality and structure through data validation and exploratory data analysis
• Learn relevant steps to validate all performed analysis
• Develop a regression model from your real gmail data
• Produce clear and effective reports to show analyses results
• Get insights from your analyses using meaningful visualizations with ggplot2

《主要特點》
- 了解資料挖掘的基礎知識，以及為何R是一個完美的工具。
- 使用流行的R套件來操作您的資料，並從中獲得有價值的業務洞察。
- 以清晰易懂的方式撰寫，並包含許多涉及真實世界資料集的實際範例。

《書籍描述》
R在許多不同行業中廣泛應用於利用資料挖掘技術，包括金融、醫學、科學研究等。本書將使您能夠使用R選擇並實施適當的資料挖掘技術，從資料中產生並展示令人印象深刻的分析結果。

本書首先詳細介紹了資料挖掘以及為何R是一個受歡迎的替代方案。您將全面了解可以在資料挖掘過程中使用的各種R套件。然後，我們將通過實際範例，包括真實世界資料集，使用這些套件來操作各種資料集。實施像k-means、SVM等算法，以及像分類和聚類分析這樣的技術，以提取有深入見解的模式和關聯。還以非常易於理解的方式涵蓋了異常檢測、回歸分析、異常檢測和網絡分析等主題。您還將使用流行的ggplot2套件來視覺化分析所獲得的見解，並幫助您做出決策。

通過閱讀本書，您將掌握資料挖掘的基本知識，以及使用流行的R套件進行各種技術部署，以充分利用您的資料。

《您將學到什麼》
- 在R環境中介紹最相關的資料挖掘套件。
- 通過資料驗證和探索性資料分析，對資料品質和結構感到自信。
- 學習驗證所有執行的分析的相關步驟。
- 從您的真實Gmail資料中開發回歸模型。
- 產生清晰有效的報告，展示分析結果。
- 使用ggplot2進行有意義的視覺化，從分析中獲得見解。