本文整理汇总了Python中Dataset.Dataset.getkPartitions方法的典型用法代码示例。如果您正苦于以下问题：Python Dataset.getkPartitions方法的具体用法？Python Dataset.getkPartitions怎么用？Python Dataset.getkPartitions使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类Dataset.Dataset的用法示例。
在下文中一共展示了Dataset.getkPartitions方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: range
# 需要导入模块: from Dataset import Dataset [as 别名]
# 或者: from Dataset.Dataset import getkPartitions [as 别名]
for it in range(5):
train_data_20, t = Dataset.getRandomPercent(train_data_all, 0.2)
train_data_50, t = Dataset.getRandomPercent(train_data_all, 0.5)
train_data_80, t = Dataset.getRandomPercent(train_data_all, 0.8)
all_training_data = [train_data_20,
train_data_50,
train_data_80,
train_data_all]
# Only run on train_data_all once.
if it > 0:
all_training_data = all_training_data[:-1]
for val in range(len(all_training_data)):
for k in k_values:
print str(it) + ": Training on: " + labels[val] + "for k value: " + str(k) + " for " + ds[0].name
# Do 2-5-N Fold Cross Validation.
cv_2 = Dataset.getkPartitions(all_training_data[val], 2)
cv_5 = Dataset.getkPartitions(all_training_data[val], 5)
cv_n = Dataset.getkPartitions(all_training_data[val],
len(all_training_data[val]))
cvs = [cv_2, cv_5, cv_n]
cross_val_accuracy = [0, 0, 0]
for cv_c in range(len(cvs)):
# Does f-Fold cross validation.
accuracy = 0
for fold in range(len(cvs[cv_c])):
td = copy.deepcopy(cvs[cv_c]) # Copy the cross validation dataset.
del td[fold] # Delete the item we're using for testing.
td_reshaped = []
for elem in td:
for item in elem:
td_reshaped.append(item)