Added classification metrics

[ekurtulus]

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