immuneML.ml_metrics package

Submodules

immuneML.ml_metrics.ClassificationMetric module

class immuneML.ml_metrics.ClassificationMetric.ClassificationMetric(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)

Bases: Enum

ACCURACY = 'accuracy_score'

AUC = 'roc_auc_score'

AUC_OVO = 'roc_auc_score_ovo'

AUC_OVR = 'roc_auc_score_ovr'

AVERAGE_PRECISION = 'average_precision_score'

BALANCED_ACCURACY = 'balanced_accuracy_score'

BRIER_SCORE = 'brier_score_loss'

CONFUSION_MATRIX = 'confusion_matrix'

F1_MACRO = 'f1_score_macro'

F1_MICRO = 'f1_score_micro'

F1_WEIGHTED = 'f1_score_weighted'

LOG_LOSS = 'log_loss'

PRECISION = 'precision_score'

PRECISION_MACRO = 'precision_score_macro'

PRECISION_MICRO = 'precision_score_micro'

PRECISION_WEIGHTED = 'precision_score_weighted'

RECALL = 'recall_score'

RECALL_MACRO = 'recall_score_macro'

RECALL_MICRO = 'recall_score_micro'

RECALL_WEIGHTED = 'recall_score_weighted'

static get_binary_only_metrics()

Metrics that required binarized labels

static get_metric(metric_name: str)

static get_probability_based_metric_types()

static get_search_criterion(metric)

static get_sklearn_score_name(metric)

immuneML.ml_metrics.ClusteringMetric module

immuneML.ml_metrics.ClusteringMetric.is_external(metric: str)

immuneML.ml_metrics.ClusteringMetric.is_internal(metric: str)

immuneML.ml_metrics.ClusteringMetric.is_valid_metric(metric: str)

immuneML.ml_metrics.MetricUtil module

class immuneML.ml_metrics.MetricUtil.MetricUtil

Bases: object

static get_metric_fn(metric: ClassificationMetric)

static score_for_metric(metric: ClassificationMetric, predicted_y, predicted_proba_y, true_y, classes, pos_class=None)

Note: when providing label classes, make sure the ‘positive class’ is sorted last. This sorting should be done automatically when accessing Label.values

immuneML.ml_metrics.ml_metrics module

immuneML.ml_metrics.ml_metrics.brier_score_loss(true_y, predicted_y, sample_weight=None, labels=None)

immuneML.ml_metrics.ml_metrics.f1_score_macro(true_y, predicted_y, sample_weight=None)

immuneML.ml_metrics.ml_metrics.f1_score_micro(true_y, predicted_y, sample_weight=None)

immuneML.ml_metrics.ml_metrics.f1_score_weighted(true_y, predicted_y, sample_weight=None)

immuneML.ml_metrics.ml_metrics.precision_score_macro(true_y, predicted_y, sample_weight=None, labels=None)

immuneML.ml_metrics.ml_metrics.precision_score_micro(true_y, predicted_y, sample_weight=None, labels=None)

immuneML.ml_metrics.ml_metrics.precision_score_weighted(true_y, predicted_y, sample_weight=None, labels=None)

immuneML.ml_metrics.ml_metrics.recall_score_macro(true_y, predicted_y, sample_weight=None, labels=None)

immuneML.ml_metrics.ml_metrics.recall_score_micro(true_y, predicted_y, sample_weight=None, labels=None)

immuneML.ml_metrics.ml_metrics.recall_score_weighted(true_y, predicted_y, sample_weight=None, labels=None)

immuneML.ml_metrics.ml_metrics.roc_auc_score(true_y, predicted_y, sample_weight=None, labels=None, multiclass: str = 'raise')

immuneML.ml_metrics.ml_metrics.roc_auc_score_ovo(true_y, predicted_y, sample_weight=None, labels=None)

immuneML.ml_metrics.ml_metrics.roc_auc_score_ovr(true_y, predicted_y, sample_weight=None, labels=None)

Module contents