Entropy¶
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class
gtda.mapper.Entropy[source]¶ Entropy of rows in a two-dimensional array.
The rows of the array are interpreted as probability vectors, after taking absolute values if necessary and normalizing. Then, their (base 2) Shannon entropies are computed and returned.
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fit(X, y=None)[source]¶ Do nothing and return the estimator unchanged.
This method exists to implement the usual scikit-learn API and hence work in pipelines.
- Parameters
X (array-like of shape (n_samples, n_features)) – Input data.
y (None) – There is no need for a target in a transformer, yet the pipeline API requires this parameter.
- Returns
self
- Return type
object
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fit_transform(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
X (array-like of shape (n_samples, n_features)) – Input data.
y (None) – There is no need for a target in a transformer, yet the pipeline API requires this parameter.
- Returns
Xt – Array of Shannon entropies.
- Return type
ndarray of shape (n_samples, 1)
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get_params(deep=True)¶ Get parameters for this estimator.
- Parameters
deep (bool, default=True) – If True, will return the parameters for this estimator and contained subobjects that are estimators.
- Returns
params – Parameter names mapped to their values.
- Return type
mapping of string to any
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set_params(**params)¶ Set the parameters of this estimator.
The method works on simple estimators as well as on nested objects (such as pipelines). The latter have parameters of the form
<component>__<parameter>so that it’s possible to update each component of a nested object.- Parameters
**params (dict) – Estimator parameters.
- Returns
self – Estimator instance.
- Return type
object
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transform(X, y=None)[source]¶ For each row in the array, take absolute values of any negative entry, normalise, and compute the Shannon entropy.
- Parameters
X (array-like of shape (n_samples, n_features)) – Input data.
y (None) – There is no need for a target in a transformer, yet the pipeline API requires this parameter.
- Returns
Xt – Array of Shannon entropies.
- Return type
ndarray of shape (n_samples, 1)
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