- Using a data set about homes, we will create a machine learning model to distinguish homes in New York from homes in San Francisco.
- Let’s say you had to determine whether a home is in San Francisco or in New York.
- In machine learning terms, categorizing data points is a classification task.Since San Francisco is relatively hilly, the elevation of a home may be a good way to distinguish the two cities.
- Based on the home-elevation data to the right, you could argue that a home above 240 ft should be classified as one in San Francisco.
- The data suggests that, among homes at or below 240 ft, those that cost more than $1776 per square foot are in New York City.
This article was written by Stephanie and Tony on R2D3.
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