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Applied Supervised Learning with R

You're reading from   Applied Supervised Learning with R Use machine learning libraries of R to build models that solve business problems and predict future trends

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Product type Paperback
Published in May 2019
Publisher
ISBN-13 9781838556334
Length 502 pages
Edition 1st Edition
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Authors (2):
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Jojo Moolayil Jojo Moolayil
Author Profile Icon Jojo Moolayil
Jojo Moolayil
Karthik Ramasubramanian Karthik Ramasubramanian
Author Profile Icon Karthik Ramasubramanian
Karthik Ramasubramanian
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Table of Contents (12) Chapters Close

Applied Supervised Learning with R
Preface
1. R for Advanced Analytics FREE CHAPTER 2. Exploratory Analysis of Data 3. Introduction to Supervised Learning 4. Regression 5. Classification 6. Feature Selection and Dimensionality Reduction 7. Model Improvements 8. Model Deployment 9. Capstone Project - Based on Research Papers Appendix

Line Charts


A line chart or line graph is a type of chart that displays information as a series of data points called markers connected by straight line segments.

ggplot uses an elegant geom() method, which helps in quickly switching between two visual objects. In the previous example, we saw geom_point() for the scatterplot. In line charts, the observations are connected by a line in the order of the variable on the x-axis. The shaded area surrounding the line represents the 95% confidence interval, that is, there is 95% confidence that the actual regression line lies within the shaded area. We will discuss more on this idea in Chapter 4, Regression.

In the following plot, we show the line chart of age and bank balance for single, married, and divorced individuals. It is not clear whether there is some trend, but one can see the pattern among the three categories:

ggplot(data = df_bank_detail) +
  geom_smooth(mapping = aes(x = age, y = balance, linetype = marital))
## 'geom_smooth()' using method = 'gam'

Figure 1.10: Line graph of age and balance

You have been reading a chapter from
Applied Supervised Learning with R
Published in: May 2019
Publisher:
ISBN-13: 9781838556334
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