# Load libraries
from sklearn.neighbors import RadiusNeighborsClassifier
from sklearn.preprocessing import StandardScaler
from sklearn import datasets

# Load data
iris = datasets.load_iris()
features = iris.data
target = iris.target

# Create standardizer
standardizer = StandardScaler()

# Standardize features
features_standardized = standardizer.fit_transform(features)

# Train a radius neighbors classifier
rnn = RadiusNeighborsClassifier(
    radius=.5, n_jobs=-1).fit(features_standardized, target)

# Create two observations
new_observations = [[ 1,  1,  1,  1]]

# Predict the class of two observations
rnn.predict(new_observations)
