mmtfPyspark.ml.datasetBalancer module
dataBalancer.py:
Creates a balanced dataset for classification problems by either
downsampling the majority classes or upsampling the minority classes.
It randomly samples each class and returns a dataset with approximately
the same number of samples in each class
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downsample(data, columnName, seed=7)[source]
Returns a balanced dataset for the given column name by downsampling
the majority classes.
The classification column must be of type String
| Parameters: | data : Dataframe
columnName : str
seed : int
|
|---|
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upsample(data, columnName, seed=7)[source]
Returns a balanced dataset for the given column name by upsampling
the majority classes.
The classification column must be of type String
| Parameters: | data : Dataframe)
columnName : str
seed : int
|
|---|
