Partitioning algorithms¶
random_partition(df, test_size, random_state=42, **kwargs)
¶
Use random partitioning algorithm
to generate training and evaluation subsets.
Wrapper around the train_test_split function
from scikit-learn.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
df
|
DataFrame
|
DataFrame with the entities to partition |
required |
test_size
|
float
|
Proportion of entities to be allocated to test subset, defaults to 0.2 |
required |
random_state
|
int
|
Seed for pseudo-random number generator algorithm, defaults to 42 |
42
|
Returns:
| Type | Description |
|---|---|
Tuple[pd.DataFrame, pd.DataFrame]
|
A tuple with the indexes of training and evaluation samples. |