src.eval.classification_uncertainty_evaluation

Classes

class src.eval.classification_uncertainty_evaluation.ClassificationUncertaintyEvaluation(**kwargs)

Class representing the result of evaluating the uncertainty for a given classification. See ClassificationUncertaintyEvaluator.

Variables:

class_names (list) – The name for each class.
X (np.ndarray) – The matrix with the coordinates of the points.
y (np.ndarray) – The point-wise classes (reference).
yhat (np.ndarray) – The point-wise classes (predictions).
Zhat (np.ndarray) – Predicted class probabilities.
pwise_entropy (np.ndarray) – The point-wise Shannon’s entropy.
weighted_entropy (np.ndarray) – The weighted Shannon’s entropy.
cluster_labels (list or np.ndarray) – The point-wise labels identifying to which cluster (in the context of the cluster-wise entropy) each point belongs to.
cluster_wise_entropy (np.ndarray) – The cluster-wise Shannon’s entropy.
class_ambiguity (np.ndarray) – The point-wise class ambiguity.
gaussian_kernel_points (int) – How many points consider for the gaussian kernel density estimation.

__init__(**kwargs)

Initialize/instantiate a ClassificationUncertaintyEvaluation.

Parameters:: kwargs – The attributes for the ClassificationUncertaintyEvaluation.

report(**kwargs)

Transform the ClassificationUncertaintyEvaluation into a ClassificationUncertaintyReport.

Returns:: The ClassificationUncertaintyReport representing the ClassificationUncertaintyEvaluation.
Return type:: :class.`.ClassificationUncertaintyReport`

plot(**kwargs)

Transform the ClassificationUncertaintyEvaluation into a ClassificationUncertaintyPlot.

Parameters:: kwargs – The key-word arguments for the plot.
Returns:: The ClassificationUncertaintyPlot representing the ClassificationUncertaintyEvaluation.
Return type:: ClassificationUncertaintyPlot