Module connectome.models.evaluation

function to evaluate the fitted model on test data

Functions

def model_evaluation(model, X_test, y_test)

Evaluates the model based on a set of metrics. Classification: Accuracy, Precision, Recall, F1 and AUC. Regression: MSE, MAE and R2. Checkout https://scikit-learn.org/stable/modules/classes.html#module-sklearn.metrics for details. For CNN make sure that the test_dataset was also transformed.

Examples:

>>> # Evaluate any model.
>>> model_evaluation(model, X_test, y_test)

Args

model

A fitted ML model

X_test

The test dataset to be evaluated

y_test

The true labels

custom_metrics

A list of custom metrics

Returns

Returns a dataframe containing model evaluations depending on prespecified metrics