palantiri.RegressionPlotHandlers module

class palantiri.RegressionPlotHandlers.OneDimensionalRegressionPlotHandler(dataset, trained_regressor, **params)

Bases: palantiri.RegressionPlotHandlers.RegressionPlotHandler

Handles all the plots related of the chosen 1D regression.

build_prediction_figure(figure_layout, step_size=0.1, x_range=None)

Building the regression figure.

:param figure_layout: figure layout - plot.ly layout object.

:param step_size: resolution of the x-axis.

:param x_range: the range of the prediction (x-axis), list of 2 numbers - indicating the start and end of the range if none will take the minimum and maximum of the data set.

class palantiri.RegressionPlotHandlers.RegressionPlotHandler(dataset, trained_regressor, **params)

Bases: palantiri.BasePlotHandlers.PlotHandler

Handles all the plots related of the chosen regressor.

build_prediction_figure(figure_layout)

Building the regression figure. :param figure_layout: figure layout - plot.ly layout object.

dataset()

The dataset

:return: The dataset as a dictionary

classmethod from_pandas_dataframe(dataframe, trained_regressor, **params)

Constructing the handler from a pandas dataframe.

:param dataframe: the dataframe form which the handler is constructed.

:param trained_regressor: sklearn regressor (trained / fitted).

:param params: other params.

:return: returns the classifier plot handler object.

plot_prediction(figure_layout=None)

Plotting the regression figure with plot.ly’s iplot function.

:param figure_layout: figure layout - plot.ly layout object.

save_prediction_figure(file_name)

Saving the prediction figure as an html file.

:param file_name: the html file name.

trained_regressor()

The trained regressor.

:return: The regressor in sklearn format.

class palantiri.RegressionPlotHandlers.TwoDimensionalRegressionPlotHandler(dataset, trained_regressor, **params)

Bases: palantiri.RegressionPlotHandlers.RegressionPlotHandler

Handles all the plots related of the chosen regressor on 2D.

build_prediction_figure(figure_layout=Layout(), x_range=None, y_range=None, step_size=0.1)

Building the regression figure.

:param figure_layout: figure layout - plot.ly layout object.

:param step_size: resolution of the x-axis.

:param x_range: the range of the prediction (x-axis), list of 2 numbers - indicating the start and end of the range if none will take the minimum and maximum of the data set. :param y_range: similar to x_range for the y-axis.