metrics.py 文件源码

def print_metrics_regression(y_true, predictions, verbose=1):
    predictions = np.array(predictions)
    predictions = np.maximum(predictions, 0).flatten()
    y_true = np.array(y_true)

    y_true_bins = [get_bin_custom(x, CustomBins.nbins) for x in y_true]
    prediction_bins = [get_bin_custom(x, CustomBins.nbins) for x in predictions]
    cf = metrics.confusion_matrix(y_true_bins, prediction_bins)
    if verbose:
        print "Custom bins confusion matrix:"
        print cf

    kappa = metrics.cohen_kappa_score(y_true_bins, prediction_bins,
                                      weights='linear')
    mad = metrics.mean_absolute_error(y_true, predictions)
    mse = metrics.mean_squared_error(y_true, predictions)
    mape = mean_absolute_percentage_error(y_true, predictions)

    if verbose:
        print "Mean absolute deviation (MAD) =", mad
        print "Mean squared error (MSE) =", mse
        print "Mean absolute percentage error (MAPE) =", mape
        print "Cohen kappa score =", kappa

    return {"mad": mad,
            "mse": mse,
            "mape": mape,
            "kappa": kappa}