giotto.base.TransformerResamplerMixin¶
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class
giotto.base.TransformerResamplerMixin¶ Mixin class for all transformers-resamplers in giotto-learn.
Methods
fit_transform(self, X[, y])Fit to data, then transform it.
fit_transform_resample(self, X, y, …)Fit to data, then transform the input and resample the target.
transform_resample(self, X, y)Fit to data, then transform it.
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__init__(self, /, *args, **kwargs)¶ Initialize self. See help(type(self)) for accurate signature.
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fit_transform(self, X, y=None, **fit_params)¶ Fit to data, then transform it.
Fits transformer to X and y with optional parameters fit_params and returns a transformed version of X.
- Parameters
- Xndarray of shape (n_samples, …)
Input data.
- yNone
There is no need for a target in a transformer, yet the pipeline API requires this parameter.
- Returns
- Xtnumpy array of shape (n_samples, …)
Transformed input.
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fit_transform_resample(self, X, y, **fit_params)¶ Fit to data, then transform the input and resample the target. Fits transformer to X and y with optional parameters fit_params and returns a transformed version of X ans a resampled version of y.
- Parameters
- Xndarray of shape (n_samples, …)
Input data.
- yndarray of shape (n_samples, )
Target data.
- Returns
- Xtndarray of shape (n_samples, …)
Transformed input.
- yrndarray of shape (n_samples, …)
Resampled target.
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transform_resample(self, X, y)¶ Fit to data, then transform it.
Fits transformer to X and y with optional parameters fit_params and returns a transformed version of X.
- Parameters
- Xndarray of shape (n_samples, …)
Input data.
- yndarray of shape (n_samples, )
Target data.
- Returns
- Xtndarray of shape (n_samples, …)
Transformed input.
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