MyMediaLite  3.02
Static Public Member Functions | Properties
Ratings Class Reference

Evaluation class for rating prediction. More...

List of all members.

Static Public Member Functions

static double ComputeCBD (double actual_rating, double prediction, double min_rating, double max_rating)
 Compute the capped binomial deviation (CBD)
static double ComputeFit (this RatingPredictor recommender)
 Computes the RMSE fit of a recommender on the training data.
static
RatingPredictionEvaluationResults 
Evaluate (this IRatingPredictor recommender, IRatings test_ratings, IRatings training_ratings=null)
 Evaluates a rating predictor for RMSE, (N)MAE, and CBD.

Properties

static ICollection< string > Measures [get]
 the evaluation measures for rating prediction offered by the class

Detailed Description

Evaluation class for rating prediction.


Member Function Documentation

static double ComputeCBD ( double  actual_rating,
double  prediction,
double  min_rating,
double  max_rating 
) [inline, static]

Compute the capped binomial deviation (CBD)

http://www.kaggle.com/c/ChessRatings2/Details/Evaluation

Returns:
The CBD of a given rating and a prediction
Parameters:
actual_ratingthe actual rating
predictionthe predicted rating
min_ratingthe lower bound of the rating scale
max_ratingthe upper bound of the rating scale
static double ComputeFit ( this RatingPredictor  recommender) [inline, static]

Computes the RMSE fit of a recommender on the training data.

Returns:
the RMSE on the training data
Parameters:
recommenderthe rating predictor to evaluate
static RatingPredictionEvaluationResults Evaluate ( this IRatingPredictor  recommender,
IRatings  test_ratings,
IRatings  training_ratings = null 
) [inline, static]

Evaluates a rating predictor for RMSE, (N)MAE, and CBD.

See http://recsyswiki.com/wiki/Root_mean_square_error and http://recsyswiki.com/wiki/Mean_absolute_error

For NMAE, see the paper by Goldberg et al.

For CBD (capped binomial deviance), see http://www.kaggle.com/c/ChessRatings2/Details/Evaluation

If the recommender can take time into account, and the rating dataset provides rating times, this information will be used for making rating predictions.

Literature:

Parameters:
recommenderrating predictor
test_ratingstest cases
training_ratingsthe training examples
Returns:
a Dictionary containing the evaluation results

Property Documentation

ICollection<string> Measures [static, get]

the evaluation measures for rating prediction offered by the class

See http://recsyswiki.com/wiki/Root_mean_square_error and http://recsyswiki.com/wiki/Mean_absolute_error


The documentation for this class was generated from the following file: