# Import packages and functions import numpy as np import pandas as pd

from sklearn.neighbors import KNeighborsClassifier from sklearn.model_selection import train_test_split

# Import dataset sleep = pd.read_csv('sleep.csv')

# Create input matrix X and output matrix y X = sleep[['bodywt', 'brainwt']] y = sleep[['vore']]

knnModel = KNeighborsClassifier(n_neighbors=6) knnModel = knnModel.fit(X.values, np.ravel(y.values))

neighbors = knnModel.kneighbors(X, return_distance=False)

# Print neighbors print(neighbors)

This dataset contains data on sleep habits for 27 randomly selected mammals. Each mammal is categorized as an omnivore, herbivore, carnivore, or insectivore.

REM sleep cycles of gray seals average 1.5 hours. Gray seals are awake on average 17.8 hours per day.

Use the kneighbors() method to find the instances in the training data that are closest to gray seals. Assign the instances, but not the distances, to neighbors.

The code contains all imports, loads the dataset, initializes the model, and applies the model to a test dataset. The neighbors line is incorrect and I have no idea why, and cannot find documentation on it to figure it out nor does my book help