From eafdea2c876e290941fbb711bfb0acf720d4034c Mon Sep 17 00:00:00 2001 From: Tanuj Vishnoi Date: Mon, 12 Nov 2018 00:23:10 +0530 Subject: [PATCH] kmeans completed --- .../Section 24 - K-Means Clustering/k-means.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/Part 4 - Clustering/Section 24 - K-Means Clustering/k-means.py b/Part 4 - Clustering/Section 24 - K-Means Clustering/k-means.py index 1d0d2b1..f87ead7 100644 --- a/Part 4 - Clustering/Section 24 - K-Means Clustering/k-means.py +++ b/Part 4 - Clustering/Section 24 - K-Means Clustering/k-means.py @@ -26,11 +26,11 @@ y_kmeans = kmeans.fit_predict(X) # Visualizing the clusters -plt.scatter(X[y_kmeans ==0, 0], X[y_kmeans == 0, 1], s = 50, c= 'red', label = 'Cluster 1') -plt.scatter(X[y_kmeans ==1, 0], X[y_kmeans == 1, 1], s = 50, c= 'yellow', label = 'Cluster 2') -plt.scatter(X[y_kmeans ==2, 0], X[y_kmeans == 2, 1], s = 50, c= 'green', label = 'Cluster 3') -plt.scatter(X[y_kmeans ==3, 0], X[y_kmeans == 3, 1], s = 50, c= 'cyan', label = 'Cluster 4') -plt.scatter(X[y_kmeans ==4, 0], X[y_kmeans == 4, 1], s = 50, c= 'magenta', label = 'Cluster 5') +plt.scatter(X[y_kmeans ==0, 0], X[y_kmeans == 0, 1], s = 50, c= 'red', label = 'Cluster 1: Careful') +plt.scatter(X[y_kmeans ==1, 0], X[y_kmeans == 1, 1], s = 50, c= 'yellow', label = 'Cluster 2: Standard') +plt.scatter(X[y_kmeans ==2, 0], X[y_kmeans == 2, 1], s = 50, c= 'green', label = 'Cluster 3: Target') +plt.scatter(X[y_kmeans ==3, 0], X[y_kmeans == 3, 1], s = 50, c= 'cyan', label = 'Cluster 4L Careless') +plt.scatter(X[y_kmeans ==4, 0], X[y_kmeans == 4, 1], s = 50, c= 'magenta', label = 'Cluster 5: Sensible') plt.scatter(kmeans.cluster_centers_[:,0], kmeans.cluster_centers_[:,1], s = 150, c= 'black', label = 'Centroids') plt.title('Clusters of clients') plt.xlabel('Annual Income (k$)')