objective- identify pattern of customers in a mall.
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
dataset = pd.read_csv("Mall_Customers.csv")
x = dataset.iloc[:,[3,4]].values
Using the elbow method to find the optimal number of clusters (use k-means++ to avoid falling into number of clusters trap)
from sklearn.cluster import KMeans
wcss = []
for i in range(1,11):
kmeans = KMeans(n_clusters = i, init = 'k-means++', random_state = 1)
kmeans.fit(x)
wcss.append(kmeans.inertia_)
plt.plot(range(1, 11), wcss)
plt.title("The elbow method")
plt.xlabel("nuber of cluster")
plt.ylabel("WCSS")
plt.show()