Nealder-Mead algorithm for finding suitable hyperparameters. More...
Static Public Member Functions | |
static double | FindMinimum (string evaluation_measure, IList< string > hp_names, IList< DenseVector > initial_hp_values, RatingPredictor recommender, ISplit< IRatings > split) |
Find the the parameters resulting in the minimal results for a given evaluation measure. | |
static double | FindMinimum (string error_measure, RatingPredictor recommender) |
Find best hyperparameter (according to an error measure) using Nelder-Mead search. |
Nealder-Mead algorithm for finding suitable hyperparameters.
static double FindMinimum | ( | string | evaluation_measure, | |
IList< string > | hp_names, | |||
IList< DenseVector > | initial_hp_values, | |||
RatingPredictor | recommender, | |||
ISplit< IRatings > | split | |||
) | [inline, static] |
Find the the parameters resulting in the minimal results for a given evaluation measure.
The recommender will be set to the best parameter value after calling this method.
evaluation_measure | the name of the evaluation measure | |
hp_names | the names of the hyperparameters to optimize | |
initial_hp_values | the values of the hyperparameters to try out first | |
recommender | the recommender | |
split | the dataset split to use |
static double FindMinimum | ( | string | error_measure, | |
RatingPredictor | recommender | |||
) | [inline, static] |
Find best hyperparameter (according to an error measure) using Nelder-Mead search.
error_measure | an error measure (lower is better) | |
recommender | a rating predictor (will be set to best hyperparameter combination) |