Skip to content

Commit afb98e6

Browse files
DhandarahAnupKumarPanwar
authored andcommitted
Creates an example of KNN algorithm using sklearn library.
1 parent 506bb5c commit afb98e6

File tree

1 file changed

+28
-0
lines changed

1 file changed

+28
-0
lines changed

machine_learning/knn_sklearn.py

+28
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,28 @@
1+
from sklearn.model_selection import train_test_split
2+
from sklearn.datasets import load_iris
3+
from sklearn.neighbors import KNeighborsClassifier
4+
5+
#Load iris file
6+
iris = load_iris()
7+
iris.keys()
8+
9+
10+
print('Target names: \n {} '.format(iris.target_names))
11+
print('\n Features: \n {}'.format(iris.feature_names))
12+
13+
#Train set e Test set
14+
X_train, X_test, y_train, y_test = train_test_split(iris['data'],iris['target'], random_state=4)
15+
16+
#KNN
17+
18+
knn = KNeighborsClassifier (n_neighbors = 1)
19+
knn.fit(X_train, y_train)
20+
21+
#new array to test
22+
X_new = [[1,2,1,4],
23+
[2,3,4,5]]
24+
25+
prediction = knn.predict(X_new)
26+
27+
print('\nNew array: \n {}'
28+
'\n\nTarget Names Prediction: \n {}'.format(X_new, iris['target_names'][prediction]))

0 commit comments

Comments
 (0)