from sklearn import datasets from DBSCAN import DBSCAN from Plot import Plot X, y = datasets.make_moons(n_samples=300, noise=0.08, shuffle=False) # Cluster the data using DBSCAN clf = DBSCAN(eps=0.17, min_samples=5) y_pred = clf.predict(X) p = Plot() p.plot_in_2d(X, y_pred, title="DBSCAN")
import pandas as pd
from Kmeans import KMeans
from Plot import Plot
dataset = pd.read_csv('data/Mall_Customers.csv')
X = dataset.iloc[:, [3, 4]].values
clf = KMeans(k=5)
y_pred = clf.predict(X)
p = Plot()
p.plot_in_2d(X, y_pred, title="K-Means Clustering")
