4 examples of 'shufflesplit sklearn' in Python

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6def split(df):
7 '''
8
9 :param df: Dataframe to be splited
10 :return: Sorted list of dataframe's splited list
11 '''
12 trainingSet, testSet = train_test_split(df, test_size=0.2)
13 sorted_trainSet = trainingSet.sort_values('user_id')
14 sorted_testSet = testSet.sort_values('user_id')
15 return sorted_testSet, sorted_trainSet
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423def _train_val_split(df, validation):
424 train_df = df
425 val_df = None
426 validation_ratio = 0.0
427
428 if isinstance(validation, float) and validation > 0:
429 train_df, val_df = train_df.randomSplit([1.0 - validation, validation])
430 validation_ratio = validation
431 elif isinstance(validation, str):
432 dtype = [field.dataType for field in df.schema.fields if field.name == validation][0]
433 bool_dtype = isinstance(dtype, BooleanType)
434 val_df = train_df.filter(
435 f.col(validation) if bool_dtype else f.col(validation) > 0).drop(validation)
436 train_df = train_df.filter(
437 ~f.col(validation) if bool_dtype else f.col(validation) == 0).drop(validation)
438
439 # Approximate ratio of validation data to training data for proportionate scale
440 # of partitions
441 timeout_ms = 1000
442 confidence = 0.90
443 train_rows = train_df.rdd.countApprox(timeout=timeout_ms, confidence=confidence)
444 val_rows = val_df.rdd.countApprox(timeout=timeout_ms, confidence=confidence)
445 validation_ratio = val_rows / (val_rows + train_rows)
446 elif validation:
447 raise ValueError('Unrecognized validation type: {}'.format(type(validation)))
448
449 return train_df, val_df, validation_ratio
220def randomSplit(self, weights, seed=None):
221 """
222
223 :param weights:
224 :param seed:
225 :return:
226 """
227 pass
167@staticmethod
168def _get_split(X, y):
169 split = ShuffleSplit(y.shape[0], n_iter=1)
170 train, validate = list(split)[0]
171 X_train, X_validate, y_train, y_validate = X[train], X[validate], y[train], y[validate]
172 return X_train, X_validate, y_train, y_validate

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