KNN

import numpy as np
import pandas as pd
import matplotlib.pyplot as ply
import seaborn as sns

%matplotlib inline

iris = sns.load_dataset("iris")

sns.lmplot("petal_length", "petal_width", data=iris, hue="species", fit_reg=False)

<seaborn.axisgrid.FacetGrid at 0x10fc2acf8>

from sklearn import neighbors
knn = neighbors.KNeighborsClassifier(n_neighbors=1)
X = iris[["petal_length", "petal_width"]]
y = iris.species.astype("category").cat.codes
knn.fit(X, y)
knn

KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',
           metric_params=None, n_jobs=1, n_neighbors=1, p=2,
           weights='uniform')

knn.get_params()

{'algorithm': 'auto',
 'leaf_size': 30,
 'metric': 'minkowski',
 'metric_params': None,
 'n_jobs': 1,
 'n_neighbors': 1,
 'p': 2,
 'weights': 'uniform'}