fairlens.metrics.HellingerDistance¶
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class
HellingerDistance
(bin_edges=None)[source]¶ Bases:
fairlens.metrics.distance.CategoricalDistanceMetric
Hellinger distance between two probability distributions.
Methods
Initialize categorical distance metric.
Check whether the input is valid.
Distance between the distribution of numerical data in x and y.
Distance between 2 aligned normalized histograms.
Returns a p-value for the test that x and y are sampled from the same distribution.
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__call__
(x, y)¶ Calculate the distance between two distributions.
- Parameters
x (pd.Series) – The data in the column representing the first group.
y (pd.Series) – The data in the column representing the second group.
- Returns
The computed distance.
- Return type
Optional[float]
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__init__
(bin_edges=None)¶ Initialize categorical distance metric.
- Parameters
bin_edges (Optional[np.ndarray], optional) – A numpy array of bin edges used to bin continuous data or to indicate bins of pre-binned data to metrics which take the distance space into account. i.e. For bins [0-5, 5-10, 10-15, 15-20], bin_edges would be [0, 5, 10, 15, 20]. See numpy.histogram_bin_edges() for more information.
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check_input
(x, y)¶ Check whether the input is valid. Returns False if x and y have different dtypes by default.
- Parameters
x (pd.Series) – The data in the column representing the first group.
y (pd.Series) – The data in the column representing the second group.
- Returns
Whether or not the input is valid.
- Return type
bool
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distance
(x, y)¶ Distance between the distribution of numerical data in x and y. Derived classes must implement this.
- Parameters
x (pd.Series) – Numerical data in a column.
y (pd.Series) – Numerical data in a column.
- Returns
The computed distance.
- Return type
float
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distance_pdf
(p, q, bin_edges)[source]¶ Distance between 2 aligned normalized histograms. Derived classes must implement this.
- Parameters
p (pd.Series) – A normalized histogram.
q (pd.Series) – A normalized histogram.
bin_edges (Optional[np.ndarray]) – bin_edges for binned continuous data. Used by metrics such as Earth Mover’s Distance to compute the distance metric space.
- Returns
The computed distance.
- Return type
float
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property
id
¶ A string identifier for the method. Used by fairlens.metrics.stat_distance(). Derived classes must implement this.
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p_value
(x, y)¶ Returns a p-value for the test that x and y are sampled from the same distribution.
- Parameters
x (pd.Series) – Numerical data in a column.
y (pd.Series) – Numerical data in a column.
- Returns
The computed p-value.
- Return type
float
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