<jupyter_start><jupyter_text><jupyter_code>from sklearn import datasets
wine = datasets.load_wine()
wine
wine.feature_names
wine.target
wine.target_names
X= wine.data
X
y= wine.target
y
from sklearn import model_selection
X_train, X_test, y_train, y_test= model_selection.train_test_split(X,y, test_size=0.3, random_state=0)
X_train.shape
X_test.shape
y_train.shape
y_test.shape
from sklearn import neighbors
knn= neighbors.KNeighborsClassifier(n_neighbors=3)
knn.fit(X,y)
knn.score(X_train, y_train)
knn.score(X_test, y_test)

import pandas as pd<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.09532062391681109, 'fraction_numerical': 0.006932409012131715, 'mean_word_length': 8.03125, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '445692', 'license': 'Apache-2.0', 'n_tokens_mistral': 240, 'n_tokens_neox': 230, 'n_words': 46, 'path': 'Classification Practice (Wine Dataset).ipynb', 'repo_name': 'lavanyamudaliyar/teachablemachine-community', 'size': '577'}