Plots the line of best fit to data showing the progression of diabetes (Y-axis) given BMI. The aim is to understand how linear regression is used in supervised machine learning.
Uses the Diabetes data set from Sklearn to find the line of best fit using y = mx + b. Values of y are predicted given m and b that are trained on the given labelled data. Data consists of BMI values (standardised to a 0 mean) and the x-axis and diabetes disease progression (after one-year baseline)
The following libraries are imported:
- matplotlib (for plotting the scatter plot)
- numpy (for arrays and maths functions)
- sklearn (for the data set)
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This project is licensed under the GNU GENERAL PUBLIC LICENSE.