R Data Mining
This book will empower you to produce and present impressive analyses from data, by selecting and implementing the appropriate data mining techniques in R. Explore a data mining crime case, where you will be requested to help resolving a real fraud case affecting a commercial company, by the mean of both basic and advanced data mining techniques.
Offered by
Difficulty Level
Intermediate
Completion Time
14h44m
Language
English
About Book
Who Is This Book For?
If you are a budding data scientist, or a data analyst with a basic knowledge of R, and want to get into the intricacies of data mining in a practical manner, this is the book for you. No previous experience of data mining is required.
R Data Mining
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 14h44m total length
Why to Choose R for Your Data Mining and Where to Start
A First Primer on Data Mining Analysing Your Bank Account Data
The Data Mining Process - CRISP-DM Methodology
Keeping the House Clean – The Data Mining Architecture
How to Address a Data Mining Problem – Data Cleaning and Validation
Looking into Your Data Eyes – Exploratory Data Analysis
Our First Guess – a Linear Regression
A Gentle Introduction to Model Performance Evaluation
Don't Give up – Power up Your Regression Including Multiple Variables
Addressing the Problem from Another Perspective Through Classification Models
The Final Clash – Random Forests and Ensemble Learning
Looking for the Culprit – Text Data Mining with R
Sharing Your Stories with Your Stakeholders through R Markdown
Epilogue
Appendix A: Dealing with Dates, Relative Paths and Functions
Related Resources
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