Linear Regression in 6 lines of Python

阿新 • • 發佈：2018-12-29

Today to perform Linear Regression quickly, we will be using the library scikit-learn. If you don’t have it already you can install it using pip:

pip install scikit-learn

So now lets start by making a few imports:

We need numpy to perform calculations, pandas to import the data set which is in csv format in this case and matplotlib to visualize our data and regression line. We will use the LinearRegression class to perform the linear regression.

Now lets perform the regression:

We have our predictions in Y_pred. Now lets visualize the data set and the regression line:

Data set in blue, Regression line in red

Data set in blue, Regression line in red

That’s it! You can use any data set of you choice, and even perform Multiple Linear Regression (more than one independent variable) using the LinearRegression class in sklearn.linear_model. Also this class uses the ordinary Least Squares method to perform this regression. So accuracy wont be high, when compared to other techniques. But if you want to make some quick predictions and get some insight into the data set given to you, then this is a very handy tool.

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