SMOTE python实现

发布时间：2019-09-03 08:55:52编辑：auto阅读（2096）

    from sklearn.neighbors import NearestNeighbors
from random import choice

X = np.array([[-1, -1],
              [-2, -1],
              [-3, -2],
              [1, 1],
              [2, 1],
              [3, 2]])
neigh = NearestNeighbors(n_neighbors = 5)
neigh.fit(X)
N=3

S = np.zeros(shape=(X.shape[0]*(N-1), X.shape[1]))
S = np.vstack((X, S))
print S
for i in xrange(X.shape[0]):
    nn = neigh.kneighbors(X[i].reshape(1, -1), return_distance=False)
    for n in xrange(N-1):
        nn_index = choice(nn[0])
        #NOTE: nn includes T[i], we don't want to select it
        while nn_index == i:
            nn_index = choice(nn[0])
        dif = X[nn_index] - X[i]
        # print dif
        gap = np.random.random()
        index = n + i * (N-1)+X.shape[0]
        print index
        S[index, :] = X[i,:] + gap * dif[:]

print S

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