파이썬 sklearn 유방암 데이터 (load_breast_cancer), 머신러닝, 딥러닝

파이썬 sklearn 유방암 데이터 (load_breast_cancer), 머신러닝, 딥러닝¶

• sklearn에서 제공하는 유방암 데이터 입니다.
• 데이터에 대한 설명은 아래 링크를 통해 확인할 수 있습니다
• https://scikit-learn.org/stable/datasets/toy_dataset.html#breast-cancer-dataset

In [4]:

import pandas as pd
from sklearn.datasets import load_breast_cancer
breast = load_breast_cancer()
df = pd.DataFrame(breast.data, columns=breast.feature_names)
df['class'] = breast.target

df.tail()

Out[4]:

	mean radius	mean texture	mean perimeter	mean area	mean smoothness	mean compactness	mean concavity	mean concave points	mean symmetry	mean fractal dimension	...	worst texture	worst perimeter	worst area	worst smoothness	worst compactness	worst concavity	worst concave points	worst symmetry	worst fractal dimension	class
564	21.56	22.39	142.00	1479.0	0.11100	0.11590	0.24390	0.13890	0.1726	0.05623	...	26.40	166.10	2027.0	0.14100	0.21130	0.4107	0.2216	0.2060	0.07115	0
565	20.13	28.25	131.20	1261.0	0.09780	0.10340	0.14400	0.09791	0.1752	0.05533	...	38.25	155.00	1731.0	0.11660	0.19220	0.3215	0.1628	0.2572	0.06637	0
566	16.60	28.08	108.30	858.1	0.08455	0.10230	0.09251	0.05302	0.1590	0.05648	...	34.12	126.70	1124.0	0.11390	0.30940	0.3403	0.1418	0.2218	0.07820	0
567	20.60	29.33	140.10	1265.0	0.11780	0.27700	0.35140	0.15200	0.2397	0.07016	...	39.42	184.60	1821.0	0.16500	0.86810	0.9387	0.2650	0.4087	0.12400	0
568	7.76	24.54	47.92	181.0	0.05263	0.04362	0.00000	0.00000	0.1587	0.05884	...	30.37	59.16	268.6	0.08996	0.06444	0.0000	0.0000	0.2871	0.07039	1

5 rows × 31 columns

[참고]

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