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  • Book Overview & Buying R for Data Science
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R for Data Science

R for Data Science

By : Toomey
3.4 (5)
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R for Data Science

R for Data Science

3.4 (5)
By: Toomey

Overview of this book

If you are a data analyst who has a firm grip on some advanced data analysis techniques and wants to learn how to leverage the features of R, this is the book for you. You should have some basic knowledge of the R language and should know about some data science topics.
Table of Contents (14 chapters)
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Chapter 2. Data Mining Sequences

Data mining is frequently used to detect sequences or patterns in data. In this chapter, we are looking for the data to follow a pattern where one event or series of events predicts another data point in a consistent manner.

This chapter describes the different ways to find patterns in your dataset:

  • Patterns to look for
  • Find patterns in data
  • Constraints

We can find patterns in many large datasets. This can range across a number of areas, such as population mix changes, frequency of cell phone use, deterioration of highways, accidents due to age, and so on. It really feels like there are many patterns and sequences just waiting to be discovered.

We can find these patterns using a number of tools in R programming. Most patterns are limited in their extent by constraints, such as time over which the sequence will be meaningful.

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R for Data Science
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