def calculate_evaluation_metrics(confusion_matrix):
    """
    Calculates the evaluation metrics of the model.
    :param confusion_matrix: The confusion matrix of the model.
    :return: dictionary, with the metrics of the model.
    """
    metrics = dict()

    metrics['precision'] = confusion_matrix.get('TP', 1) / (
            confusion_matrix.get('TP', 1) + confusion_matrix.get('FP', 1))
    metrics['recall'] = confusion_matrix.get('TP', 1) / (
            confusion_matrix.get('TP', 1) + confusion_matrix.get('FN', 1))
    metrics['f1_score'] = 2 * metrics['precision'] * metrics['recall'] / (metrics['precision'] + metrics['recall'])

    return metrics