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Added classification metrics #626

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@ekurtulus ekurtulus commented Oct 29, 2020

When I was working with Knet, I felt the need of classification metrics for a better evaluation of my model, but saw that Knet does not offer such a functionality, so I added a classification metrics module that includes:

  • A general use confusion matrix struct
  • Classification metrics
  • A visualization function for both classification metrics and the confusion matrix
  • The following functions:
confusion_params,
confusion_matrix,
class_confusion,
visualize, 
classification_report
condition_positive
condition_negative
predicted_positive
predicted_negative
correctly_classified
incorrectly_classified
sensitivity_score
recall_score
specificity_score
precision_score
positive_predictive_value
accuracy_score
balanced_accuracy_score
negative_predictive_value
false_negative_rate
false_positive_rate
false_discovery_rate
false_omission_rate
f1_score
prevalence_threshold
threat_score
matthews_correlation_coeff
fowlkes_mallows_index
informedness
markedness
cohen_kappa_score
hamming_loss
jaccard_score

@ekurtulus ekurtulus closed this Nov 14, 2020
@ekurtulus ekurtulus reopened this Nov 14, 2020
@ekurtulus ekurtulus closed this Nov 14, 2020
@ekurtulus ekurtulus reopened this Nov 14, 2020
@ekurtulus ekurtulus changed the title Added confusion matrix and new tutorials Added classification metrics Dec 27, 2020
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