TP_Clustering/artificial/kmeans.py
2021-10-28 17:41:43 +02:00

26 lines
510 B
Python

from scipy.io import arff
import numpy as np
from sklearn.cluster import KMeans
from sklearn.datasets import make_blobs
import matplotlib.pyplot as plt
#K_means algorithm
n_clusters = 3
data = arff.loadarff('2d-4c-no9.arff')[0]
data_final = []
x_list = []
y_list = []
for (x, y, z) in data :
x_list.append(x)
y_list.append(y)
data_final.append([x,y])
kmeans = KMeans(n_clusters, init='k-means++').fit(data_final)
colors = kmeans.labels_
plt.scatter(x_list, y_list, c=colors, s=5)
plt.show()