scikit-learn - 4(모델 맛보기)

의사 결정 트리(DecisionTreeClassifier)

검증데이터 분리

from sklearn.model_selection import train_test_split

x_train, x_test, y_train, y_test = train_test_split(
    cancer_df.drop('target', axis = 1), cancer_df['target'], test_size = 0.3, random_state = 1004)

model

from sklearn.tree import DecisionTreeClassifier

model = DecisionTreeClassifier()

model.fit(x_train, y_train)
pred = model.predict(x_test)
pred

predict(accuracy_score)

from sklearn.metrics import accuracy_score

accuracy_score(y_test, pred)

선형회귀(LinearRegression)

검증데이터 분리

# 검증데이터 분리
from sklearn.model_selection import train_test_split

x_train, x_test, y_train, y_test = train_test_split(
    diabetes_df.drop('target', axis = 1), diabetes_df['target'], test_size = 0.3, random_state = 1004)

model

from sklearn.linear_model import LinearRegression

model = LinearRegression()

model.fit(x_train, y_train)
pred = model.predict(x_test)
pred

predict(MSE)

MSE : mean_squared_error

from sklearn.metrics import mean_squared_error

mean_squared_error(y_test, pred)

낮을 수록 좋은거임