Adding Python ML examples of clustering data points.

[pingpong.git] / python_ml / dlink_clustering.py

diff --git a/python_ml/dlink_clustering.py b/python_ml/dlink_clustering.py
new file mode 100644 (file)
index 0000000..badd5b1
--- /dev/null
+++ b/python_ml/dlink_clustering.py
@@ -0,0 +1,6 @@
+from sklearn.cluster import KMeans
+import numpy as np
+X = np.array([[132, 192], [117, 960], [117, 962], [1343, 0], [117, 1109], [117, 1110], [117, 1111], [117, 1116], [117, 1117], [117, 1118], [117, 1119], [1015, 0], [117, 966]])
+kmeans = KMeans(n_clusters=5, random_state=0).fit(X)
+print(kmeans.labels_)
+print(kmeans.labels_.tolist().count(3))