Kmean_malware

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

from sklearn.cluster import KMeans
from sklearn.metrics import silhouette_score

import warnings
warnings.simplefilter('ignore')

# Load the dataset
malware_dataset = pd.read_csv('.../MalwareArtifacts.csv')

samples = malware_dataset.iloc[:, [1,2,3,4]].values
targets = malware_dataset.iloc[:, 8].values

k_means = KMeans(n_clusters=2, max_iter=300)
k_means.fit(samples)

print("K-means labels: " + str(k_means.labels_))

print ("\nK-means Clustering Results:\n\n", pd.crosstab(targets, k_means.labels_, rownames=["Observed"], colnames=["Predicted"]))

print ("\nSilhouette coefficient: %0.3f" % silhouette_score(samples, k_means.labels_, metric='euclidean'))