小编Pan*_*aga的帖子

我试图在python中实现k-fold交叉验证算法.我知道SKLearn提供了一个实现但仍然......这是我现在的代码.

from sklearn import metrics
import numpy as np

class Cross_Validation:

@staticmethod
def partition(vector, fold, k):
    size = vector.shape[0]
    start = (size/k)*fold
    end = (size/k)*(fold+1)
    validation = vector[start:end]
    if str(type(vector)) == "<class 'scipy.sparse.csr.csr_matrix'>":
        indices = range(start, end)
        mask = np.ones(vector.shape[0], dtype=bool)
        mask[indices] = False
        training = vector[mask]
    elif str(type(vector)) == "<type 'numpy.ndarray'>":
        training = np.concatenate((vector[:start], vector[end:]))
    return training, validation

@staticmethod
def Cross_Validation(learner, k, examples, labels):
    train_folds_score = []
    validation_folds_score = []
    for fold in range(0, k):
        training_set, validation_set = Cross_Validation.partition(examples, …