Centering (Center)
API reference
- class sequentia.preprocessing.Center(independent=True)[source]
Centers the observation sequence features around their means. Results in zero-mean features.
- Parameters
- independent: bool
Whether to independently compute the mean to scale each observation sequence.
Examples
>>> # Create some sample data >>> X = [np.random.random((10 * i, 3)) for i in range(1, 4)] >>> # Center the data >>> X = Center()(X)
- fit(X, validate=True)[source]
Fit the transformation on the provided observation sequence(s) (without transforming them).
- Parameters
- X: numpy.ndarray (float) or list of numpy.ndarray (float)
An individual observation sequence or a list of multiple observation sequences.
- validate: bool
Whether or not to validate the input sequences.
- transform(x)[source]
Applies the transformation to a single observation sequence.
- Parameters
- X: numpy.ndarray (float)
An individual observation sequence.
- Returns
- transformed:class:numpy:numpy.ndarray (float)
The transformed input observation sequence.
- is_fitted()[source]
Check whether or not the transformation is fitted on some observation sequence(s).
- Returns
- fitted: bool
Whether or not the transformation is fitted.
- fit_transform(X, validate=True)
Fit the transformation with the provided observation sequence(s) and transform them.
- Parameters
- X: numpy.ndarray (float) or list of numpy.ndarray (float)
An individual observation sequence or a list of multiple observation sequences.
- validate: bool
Whether or not to validate the input sequences.
- Returns
- transformed:class:numpy:numpy.ndarray (float) or list of
numpy.ndarray(float) The transformed input observation sequence(s).
- transformed:class:numpy:numpy.ndarray (float) or list of
- __call__(X, validate=True)
Applies the transformation to the observation sequence(s).
- Parameters
- X: numpy.ndarray (float) or list of numpy.ndarray (float)
An individual observation sequence or a list of multiple observation sequences.
- validate: bool
Whether or not to validate the input sequences.
- Returns
- transformed:class:numpy:numpy.ndarray (float) or list of
numpy.ndarray(float) The transformed input observation sequence(s).
- transformed:class:numpy:numpy.ndarray (float) or list of