# Linear Regression in One Variable

This is a supervised learning algorithm where we estimate the value of a dependent target variable using a linear combination of operations on an independent variable.

It is also called **Univariate Linear Regression**.

There is one input and one output.

Since it is a form of supervised learning, the end result is already known.

The general hypothesis function is of the form:

$$h\_θ(x) = θ\_0 + θ\_1x$$

![](https://1423730981-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-M5-0RGuSGVoyMc2kCFR%2F-M5-0RgMLg-NeST4zMsc%2F-M5-0U9AThWWJLnEGZbl%2FLinearRegression.png?generation=1586990807569114\&alt=media)