neuraxle.steps.features

Featurization Steps

You can find here steps that featurize your data.

Classes

Cheap3DTo2DTransformer()

Prebuild class to featurize 3D data into 2D data for simple classification or regression, for instance.

FFTPeakBinWithValue()

Compute peak fft bins (int), and their magnitudes’ value (float), to concatenate them.

class neuraxle.steps.features.Cheap3DTo2DTransformer[source]

Prebuild class to featurize 3D data into 2D data for simple classification or regression, for instance.

You can enable, or disable features using hyperparams :

step = Cheap3DTo2DTransformer().set_hyperparams(hyperparams={
    'FFT__enabled': True,
    'NumpyMean__enabled': True,
    'NumpyMedian__enabled': True,
    'NumpyMin__enabled': True,
    'NumpyMax__enabled': True
})
_abc_impl = <_abc_data object>
class neuraxle.steps.features.FFTPeakBinWithValue[source]

Compute peak fft bins (int), and their magnitudes’ value (float), to concatenate them. This is intended to be used only after a NumpyFFT absolute step.

_abc_impl = <_abc_data object>