Prediction Options

PredictionOptions

A configurable base options class for relevance-based predictions, including predict, maxfit, and grid models. This class provides a comprehensive list of all possible input parameters, ensuring flexibility across different prediction models. While some parameters are shared across inherited models, setting an unused option for a specific model will have no effect, ensuring compatibility and ease of use.

Key	Type	Description
threshold	float or ndarray [1-by-], optional (default=None)	Evaluation threshold to determine whether observations will be included or excluded from the censor function in the partial-sample regression. If not specified (None), the censor function will evaluate across threshold from [0, 0.90) in 0.10 increments.
is_threshold_percent	bool, optional (default=True)	Specify whether threshold(s) are in percentage (decimal) units.
most_eval	bool, optional (default=True)	Specify the of the censor evaluation of the threshold.
eval_type	str, optional (default="both")	Specify the evaluation censor type: relevance, similarity, or both.

MaxFitOptions(PredictionOptions)

A specialized options class for MaxFit problems.

Inherits from `PredictionOptions` and adds additional parameters specific to MaxFit prediction tasks. This class ensures that users can leverage all standard prediction options while also configuring MaxFit-specific behaviors to optimize model fitting based on the highest (adjusted) fit.

Key	Type	Description
threshold_range	tuple or ndarray [1-by-], optional (default=[0, 0.20, 0.50, 0.80])	Min/max or range for evaluating maxfit threshold, by default (0, 0.20, 0.50, 0.80). If an ndarray is passed in, max fit evaluates over the specified threshold values in the specified row vector.
stepsize	float, optional (default=0.20)	Step size to evaluate range of thresholds for solving max fit. Decreasing the step size will increase the resolution of the grid (number of grid cells).
objective	str, optional (default=adjusted_fit)	Specify the objective function of the max fit solver, by default this is adjusted fit.

GridOptions(MaxFitOptions)

A specialized options class for grid prediction tasks.

Inherits from `MaxFitOptions` and introduces additional parameters specific to grid-based prediction models. This class allows users to configure both standard MaxFit options and advanced settings required for relevance-based grid predictions, enabling flexible and optimized grid searches across thresholds and variable combinations.

Key	Type	Description
attribute_combi	ndarray [-by-], optional (default=None)	Matrix of binary row vectors to indicate variable choices. Each row is a combination of variables to evaluate. If not specified, function will evaluate all possible combinations.
k	float, optional (default=1)	Lower bound for the number of variables to include for any combination Q, by default 1.