Using SVM to cluster people by using scikit-learn

Let's try out some support vector machines here. Fortunately, it's a lot easier to use than it is to understand. We're going to go back to the same example I used for k-means clustering, where I'm going to create some fabricated cluster data about ages and incomes of a hundred random people.

If you want to go back to the k-means clustering section, you can learn more about kind of the idea behind this code that generates the fake data. And if you're ready, please consider the following code:

import numpy as np 
 
#Create fake income/age clusters for N people in k clusters 
def createClusteredData(N, k): 
    pointsPerCluster = float(N)/k 
    X = [] 
    y = [] 
    for i in range (k): 
        incomeCentroid = np.random.uniform(20000.0, 200000.0) 
        ageCentroid = np.random.uniform(20.0, 70.0) 
 ...