RegressorDiagnostic

class protopipe.mva.RegressorDiagnostic(model, feature_name_list, target_name, data_train, data_test, output_name)

Bases: protopipe.mva.ModelDiagnostic

Class to plot several diagnostic plot for regression

Parameters

model: sklearn.base.BaseEstimator

Scikit model

feature_name_list: str

List of features

target_name: str

Name of target (e.g. mc_energy)

data_train: `~pandas.DataFrame`

Data frame

data_test: `~pandas.DataFrame`

Data frame

Methods Summary

add_image_model_output(data, col_name)
plot_resolution_distribution(ax, y_true, y_reco)	Compute bias and resolution with a gaussian fit and returns a plot with the fit results and the migration distribution

Methods Documentation

add_image_model_output(data, col_name)

static plot_resolution_distribution(ax, y_true, y_reco, nbin=100, fit_range=[- 3, 3], fit_kwargs={}, hist_kwargs={})

Compute bias and resolution with a gaussian fit and returns a plot with the fit results and the migration distribution