Visualization of Regression Model
To visualize the linear regression model in the R Language, we use the plot() function to plot the scatter plot of data points and then use the abline() pot to plot the regression line.
Syntax:
plot( datax, datay )
abline( linear_model)
Parameter:
- datax and datay: determine the value for the x-axis and y-axis variables.
- linear_model: determines the linear model for visualization.
Example: Here, is a visualization of a linear model with intercept.
R
# sample data framesample_data <- data.frame( x1= c(2,3,5,4,8), x2= c(0,3,5,6,23), y= c(1,6,9,15,29)) # fit linear modellinear_model <- lm(y ~ x1+x2, data=sample_data) # visualize linear modelplot( sample_data$x1, sample_data$y, col= "blue", pch=16 )points( sample_data$x2, sample_data$y, col="red", pch=16 )abline(linear_model, col="green", lwd=2 ) |
Output:
Remove Intercept from Regression Model in R
In this article, we will discuss how to remove intercept from the Regression model in the R Programming Language.
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