sklearn之load

from sklearn.datasets import load_iris from sklearn.preprocessing import MinMaxScaler from sklearn.cluster import KMeans iris = load_iris() iris_data = iris['data'] iris_target = iris['target'] iris_names = iris['feature_names'] scale = MinMaxScaler().fit(iris_data)#训练模型 iris_dataScale = scale.transform(iris_data) kmeans = KMeans(n_clusters=3,random_state=123).fit(iris_dataScale) print(kmeans) result = kmeans.predict([[1.5,1.5,1.5,1.5]]) print(result[0])