<jupyter_start><jupyter_text>카테고리는 분류형이다<jupyter_code>df.info()
df.describe()<jupyter_output><empty_output><jupyter_text>--------sklearn에서 데이터가져와서할거얌<jupyter_code>from sklearn.datasets import load_breast_cancer
cancer=load_breast_cancer()
type(cancer)
cancer
x=cancer.data
y=cancer.target
x.shape, y.shape
import pandas as pd
df=pd.DataFrame(x)
df
import matplotlib.pyplot as plt
import seaborn as sns
df.info()
df.describe()
sns.distplot(x[0])
from sklearn.model_selection import train_test_split
x_train, x_test , y_train , y_test = train_test_split(x,y)
x_train.shape , x_test.shape , y_train.shape , y_test.shape
from sklearn.preprocessing import StandardScaler
scaler = StandardScaler()
scaler.fit(x_train)
x_train = scaler.transform(x_train)
x_train
sns.distplot(x_train[5])
from sklearn.linear_model import LogisticRegression
log_train = LogisticRegression()
log_train.fit(x_train,y_train)
log_train.score(x_train,y_train)
log_train.score(x_test,y_test)
x_test = scaler.transform(x_test)
log_train.score(x_test,y_test)<jupyter_output><empty_output>
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