Add threshold value limits for multiclass metrics (#411)

nannyml/performance_estimation/confidence_based/metrics.py

@@ -2326,6 +2326,8 @@ def __init__(
  chunker=chunker,
  threshold=threshold,
  components=[('ROC AUC', 'roc_auc')],
+ lower_threshold_value_limit=0,
+ upper_threshold_value_limit=1,
  )
  self.y_pred_proba: Dict[str, str]
  self.classes: List[str] = [""]
@@ -2463,6 +2465,8 @@ def __init__(
  chunker=chunker,
  threshold=threshold,
  components=[('F1', 'f1')],
+ lower_threshold_value_limit=0,
+ upper_threshold_value_limit=1,
  )
 
  # sampling error:
@@ -2577,6 +2581,8 @@ def __init__(
  chunker=chunker,
  threshold=threshold,
  components=[('Precision', 'precision')],
+ lower_threshold_value_limit=0,
+ upper_threshold_value_limit=1,
  )
 
  # sampling error
@@ -2692,6 +2698,8 @@ def __init__(
  chunker=chunker,
  threshold=threshold,
  components=[('Recall', 'recall')],
+ lower_threshold_value_limit=0,
+ upper_threshold_value_limit=1,
  )
 
  # sampling error
@@ -2807,6 +2815,8 @@ def __init__(
  chunker=chunker,
  threshold=threshold,
  components=[('Specificity', 'specificity')],
+ lower_threshold_value_limit=0,
+ upper_threshold_value_limit=1,
  )
 
  # sampling error
@@ -2927,6 +2937,8 @@ def __init__(
  chunker=chunker,
  threshold=threshold,
  components=[('Accuracy', 'accuracy')],
+ lower_threshold_value_limit=0,
+ upper_threshold_value_limit=1,
  )
 
  # sampling error
@@ -3356,6 +3368,8 @@ def __init__(
  chunker=chunker,
  threshold=threshold,
  components=[('Average Precision', 'average_precision')],
+ lower_threshold_value_limit=0,
+ upper_threshold_value_limit=1,
  )
  # FIXME: Should we check the y_pred_proba argument here to ensure it's a dict?
  self.y_pred_proba: Dict[str, str]