Model API Reference

assert_model

A builder for model performance assertions.

from ml_assert import assert_model

# Create model assertions
assert_model(y_true, y_pred, y_scores) \
    .accuracy(min_score=0.80) \
    .precision(min_score=0.80) \
    .recall(min_score=0.80) \
    .f1(min_score=0.80) \
    .roc_auc(min_score=0.90) \
    .validate()

Methods

accuracy(min_score)

Asserts minimum accuracy score.

Parameters: - min_score: Minimum acceptable accuracy score (0.0 to 1.0)

Returns: - self for method chaining

precision(min_score)

Asserts minimum precision score.

Parameters: - min_score: Minimum acceptable precision score (0.0 to 1.0)

Returns: - self for method chaining

recall(min_score)

Asserts minimum recall score.

Parameters: - min_score: Minimum acceptable recall score (0.0 to 1.0)

Returns: - self for method chaining

f1(min_score)

Asserts minimum F1 score.

Parameters: - min_score: Minimum acceptable F1 score (0.0 to 1.0)

Returns: - self for method chaining

roc_auc(min_score)

Asserts minimum ROC AUC score.

Parameters: - min_score: Minimum acceptable ROC AUC score (0.0 to 1.0)

Returns: - self for method chaining

validate()

Executes all chained assertions.

Raises: - AssertionError if any assertion fails