Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
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

Arrow left icon
Product type Paperback
Published in May 2019
Publisher
ISBN-13 9781838556334
Length 502 pages
Edition 1st Edition
Languages
Arrow right icon
Authors (2):
Arrow left icon
Jojo Moolayil Jojo Moolayil
Author Profile Icon Jojo Moolayil
Jojo Moolayil
Karthik Ramasubramanian Karthik Ramasubramanian
Author Profile Icon Karthik Ramasubramanian
Karthik Ramasubramanian
Arrow right icon
View More author details
Toc

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
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image