Metric Functions
Description
This module contains the functions to calculate the metrics accuracy, Cohen’s kappa coefficient, logarithmic loss and root-mean-squared error. These functions are used to evaluate the performance of the given data.
- bciflow.modules.analysis.metric_functions.accuracy(results: DataFrame) float [source]
Calculates the accuracy given the correct labels and the predicted probabilities.
- Parameters:
results (pandas.DataFrame) – Dataframe with the true label and predicted probabilities.
- Returns:
Accuracy value.
- Return type:
float
- bciflow.modules.analysis.metric_functions.kappa(results: DataFrame) float [source]
Calculates the Cohen’s kappa coefficient given the correct labels and the predicted probabilities.
- Parameters:
results (pandas.DataFrame) – Dataframe with the true label and predicted probabilities.
- Returns:
Kappa value
- Return type:
float
- bciflow.modules.analysis.metric_functions.logloss(results: DataFrame) float [source]
Calculates the logarithmic loss given the correct labels and the predicted probabilities.
- Parameters:
results (pandas.DataFrame) – Dataframe with the true label and predicted probabilities.
- Returns:
Logarithmic loss value.
- Return type:
float
- bciflow.modules.analysis.metric_functions.rmse(results: DataFrame) float [source]
Calculates the root-mean-squared error given the correct labels and the predicted probabilities.
- Parameters:
results (pandas.DataFrame) – Dataframe with the true label and predicted probabilities.
- Returns:
Root-mean-squared error value.
- Return type:
float