`doenut.models.model`

Module Contents

Classes

A simple linear regression model.

class doenut.models.model.Model(data: doenut.data.data_set.DataSet, fit_intercept: bool)[source]

A simple linear regression model.

Note

This class mostly exists as a base - you probably want AveragedModel

Parameters:

data (doenut.data.DataSet) – The inputs and responses for this model
fit_intercept (bool) – Whether to fit the intercept of the model to the axis

get_predictions_for(inputs: pandas.DataFrame) → pandas.DataFrame[source]

Generates the predictions of the model for a set of inputs

Parameters:: inputs (pd.DataFrame) – The inputs to test against.
Returns:: the predictions from the model
Return type:: pd.DataFrame

get_r2_for(data: doenut.data.data_set.DataSet)[source]

Calculate the R2 Pearson coefficient for a given pairing of inputs and responses.

Parameters:: data (doenut.data.DataSet) – The data to test.
Returns:: The calculated R2 value as a float
Return type:: float