nano-bot01/K-means-clustering-on-IRIS-dataset

K means clustering on IRIS dataset on Sapel length and Sapel width

K-means-clustering-on-IRIS-dataset

K means clustering on IRIS dataset on Sapel length and Sapel width

Importing the Dependencies

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.cluster import KMeans

Import data from dataset

dataset = pd.read_csv("C://Users//DITU//Documents//Jupyter//iris_dataset.csv")

Take two attributes for training model with K-Means clustering

Here, I have taken Sepal Length and Sepal Width as X and Y attributes respectively.

X = dataset["sepal length (cm)"]
X

Y = dataset["sepal width (cm)"]
Y

Zip the dataset into one list

dataset_new = list(zip(X,Y))
dataset_new

Train model

iris_model = KMeans(n_clusters = 4)
iris_model.fit(dataset_new)

Visualizing the clusters

plt.figure(figsize=(16,9))
plt.scatter(X,Y, c= iris_model.labels_, marker= "*", s = 300)
plt.xlabel("Iris Sepal Length", fontsize = 12)
plt.ylabel("Iris Sepal Width", fontsize = 12)
plt.title("K Means cluster", fontsize = 16)

plt.show()

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Ankit Nainwal