/Iris-Number-Of-Clusters

Primary LanguageJupyter Notebook

1-Importing Data and Exploring

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

df = pd.read_csv('./Iris.csv')
df.head()
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Id SepalLengthCm SepalWidthCm PetalLengthCm PetalWidthCm Species
0 1 5.1 3.5 1.4 0.2 Iris-setosa
1 2 4.9 3.0 1.4 0.2 Iris-setosa
2 3 4.7 3.2 1.3 0.2 Iris-setosa
3 4 4.6 3.1 1.5 0.2 Iris-setosa
4 5 5.0 3.6 1.4 0.2 Iris-setosa

2- Elbow Method To Find Number of Clusters

from sklearn.cluster import KMeans

X = df.iloc[:,:-1]
y = df.iloc[:,-1]

wc = []

for i in range(1,11):
    km = KMeans(n_clusters=i,
                init='k-means++',
                max_iter=200,
                n_init=10,
                random_state=42
               )
    km.fit(X)
    wc.append(km.inertia_)
    
plt.plot(range(1,11), wc)
[<matplotlib.lines.Line2D at 0x7fc7f8f1f9d0>]

png

From Elbow method clusters num could be 3

3- Training The Model

model = KMeans(
    n_clusters=3,
    init='k-means++',
    max_iter=200,
    n_init=10,
    random_state=42
)

y_predict = model.fit_predict(X)
print(model.cluster_centers_)
y_predict
[[125.5     6.588   2.974   5.552   2.026]
 [ 25.5     5.006   3.418   1.464   0.244]
 [ 75.5     5.936   2.77    4.26    1.326]]





array([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
       1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
       2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
       2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], dtype=int32)

4- Plotting The Clusters

plt.scatter(X.iloc[y_predict == 0, 0], X.iloc[y_predict == 0, 1], 
            s = 100, c = 'red', label = 'Iris-setosa')
plt.scatter(X.iloc[y_predict == 1, 0], X.iloc[y_predict == 1, 1], 
            s = 100, c = 'blue', label = 'Iris-versicolour')
plt.scatter(X.iloc[y_predict == 2, 0], X.iloc[y_predict == 2, 1],
            s = 100, c = 'green', label = 'Iris-virginica')
plt.scatter(model.cluster_centers_[:, 0], model.cluster_centers_[:,1], 
            s = 100, c = 'yellow', label = 'Centroids')
plt.legend()
<matplotlib.legend.Legend at 0x7fc84a38db50>

png