knn_iris.py

gistfile1.txt

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

from sklearn import datasets
from sklearn.cross_validation import train_test_split
from sklearn.neighbors import KNeighborsClassifier

names = ['sepal_length', 'sepal_width', 'petal_length', 'petal_width', 'class']
iris = datasets.load_iris()
X = iris.data[:, :2]  # we only take the first two features.
y = iris.target

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=42)

knn = KNeighborsClassifier(n_neighbors=20)
knn.fit(X_train,y_train)

pred = knn.predict(X_test)
print(pred)

# Making the Confusion Matrix
from sklearn.metrics import confusion_matrix
cm = confusion_matrix(y_test, pred)
print(cm)