인공지능 실습

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from sklearn.datasets import load_iris
iris = load_iris()
 
from sklearn.model_selection import train_test_split
 
# 입력과 출력을 설정한다. 
X = iris.data
y = iris.target
 
# 전체 데이터를 학습 데이터와 테스트 데이터 비율 (80:20)으로 분할한다. 
X_train,X_test,y_train,y_test = train_test_split(X,y,test_size=0.2,random_state=4)
print(X_train.shape)
 
from sklearn.neighbors import KNeighborsClassifier
from sklearn import metrics
 
# 학습 단계
knn = KNeighborsClassifier(n_neighbors=6)
knn.fit(X_train, y_train)
 
# 테스트 단계
y_pred = knn.predict(X_test)
 
# 정확도 점수 출력
scores = metrics.accuracy_score(y_test, y_pred)
print(scores)
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