LDA分类与降维

# lda 分类 原理在于投影后，类之间的距离最大，类内距离最小的原则


from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
from sklearn import datasets

def createdata():
    iris=datasets.load_iris()
    x=iris.data
    y=iris.target
    return x,y

x,y=createdata()
print(x)
print(y)

clf=LinearDiscriminantAnalysis()
clf.fit(x,y)
print(clf.predict(x))


# lda降维

lda=LinearDiscriminantAnalysis(n_components=2)
ldajw=lda.fit(x,y)
X=ldajw.transform(x)
print(X)