Linear Regression and Support Vector Machine are two of the most common classical machine learning algorithms, supported by Scikit Learn of course. We'll take a look at how to build models for house price prediction using the two algorithms.
Using Core ML with Scikit-Learn machine learning
Building and converting the Scikit Learn models
First, let's get a dataset of house prices, available for download at https://wiki.csc.calpoly.edu/datasets/wiki/Houses. The downloaded RealEstate.csv file looks like this:
MLS,Location,Price,Bedrooms,Bathrooms,Size,Price/SQ.Ft,Status
132842,Arroyo Grande,795000.00,3,3,2371,335.30,Short Sale
134364,Paso Robles,399000.00,4,3,2818,141.59,Short Sale
135141,Paso Robles,545000.00,4,3,3032...