Classification_Naive Bayes

Naive Bayes

Time: 2021-01-14 Thursday 17:30

import sklearn.cluster as sc
import numpy as np

Download Data

x = []
with open('../data/multiple3.txt', 'r') as f:
    for line in f.readlines():
        # 每一行数据按照,分隔
        data = [float(substr) for substr in line.split(',')]
        print(data)
        x.append(data)

x = np.array(x)

# 创建模型
model = sc.KMeans(4)
# n_clusters为聚类数量
model.fit(x)
# 获取聚类中心
centers = model.cluster_centers_

Get the clustering result label.

pred_y = model.labels_
print(centers)
print(pred_y)
import matplotlib.pyplot as mp

mp.figure('Kmeans', facecolor='lightgray')
mp.title('Kmeans', fontsize=16)
mp.xlabel('x', fontsize=14)
mp.ylabel('y', fontsize=14)
mp.scatter(centers[:, 0], centers[:, 1], marker="+", c='black', s=200)
mp.scatter(x[:, 0], x[:, 1], c=pred_y, cmap='brg')
mp.show()