통계 프로그램 R 기술서 [쉽게 배우기]

목차

1. The Basic Stat
2. Data Mining
3. Data manipulation
4. Data management Statistical Summary
5. Plots for analysis
6. Full analysis: regression
7. Correlation
8. Modeling & Regression

본문내용

Data Mining
Data Mining with Rattle and R, Graham Williams, Springer
Data Mining, Ian H. Witten & Eibe Frank, Elsevier
Data Mining, Charu C. Aggarwal, Springer
Data Wrangling with Python, Jacqueline Kazil & Katharine Jarmul, O’Reilly
Data Mining and Analysis : Fundamental Concepts and Algorithms, Mohammed J. Zaki & Wagner Meira JR.
Cassandra Data Modeling and Analysis, C. Y. Kan, PACKT

Basically, There are many types of data and so does the methods for data mining. However, In this book, we will only concern the practical and basic methods for data mining.

First, there is a conventional way to gather data. You could download data you need by searching and downloading .csv, .xlsx and others. Definitely, it is the easiest way to gather data for your research. However, It needs lots of times and hardworking. And, of course, these data collected could be neither enough big data nor ‘Big-Data’. In this sense, I strongly recommend you to learn following techniques.

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