diff --git a/KNN.py b/KNN.py
new file mode 100644
index 0000000..0ae125a
--- /dev/null
+++ b/KNN.py
@@ -0,0 +1,32 @@
+# Importing the libraries
+import numpy as np
+import matplotlib.pyplot as plt
+import pandas as pd
+import os
+os.chdir('C:\\Users\\saket\\Desktop\\cricket machine learning')
+# Importing the dataset
+dataset = pd.read_csv('worldCup.csv')
+X = dataset.iloc[:, [1,2,3,4,5,6,7,8]].values
+y = dataset.iloc[:, 9].values
+
+# Splitting the dataset into the Training set and Test set
+from sklearn.cross_validation import train_test_split
+X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.2, random_state = 0)
+
+# Feature Scaling
+from sklearn.preprocessing import StandardScaler
+sc = StandardScaler()
+X_train = sc.fit_transform(X_train)
+X_test = sc.transform(X_test)
+
+# Fitting K-NN to the Training set
+from sklearn.neighbors import KNeighborsClassifier
+classifier = KNeighborsClassifier(n_neighbors = 5, metric = 'minkowski', p = 2)
+classifier.fit(X_train, y_train)
+
+# Predicting the Test set results
+y_pred = classifier.predict(X_test)
+
+# Making the Confusion Matrix
+from sklearn.metrics import confusion_matrix
+cm = confusion_matrix(y_test, y_pred)
\ No newline at end of file