src.fairreckitlib.evaluation.metrics.metric_constants

 1"""This module contains metric constants that are used in other modules.
 2
 3Constants:
 4
 5    KEY_METRIC_PARAM_K: the key that is used for the metric parameter K.
 6    KEY_METRIC_EVALUATION: the key that is used to identify a metric evaluation.
 7    KEY_METRIC_SUBGROUP: the key that is used to identify a metric subgroup.
 8
 9Enumerations:
10
11    MetricCategory: the category of evaluation for a metric.
12    Metric: the names of various metrics.
13
14This program has been developed by students from the bachelor Computer Science at
15Utrecht University within the Software Project course.
16© Copyright Utrecht University (Department of Information and Computing Sciences)
17"""
18
19import enum
20
21KEY_METRIC_PARAM_K = 'K'
22KEY_METRIC_EVALUATION = 'evaluation'
23KEY_METRIC_SUBGROUP = 'subgroup'
24
25
26class MetricCategory(enum.Enum):
27    """Metric category of evaluation."""
28
29    ACCURACY = 'Accuracy'
30    RATING = 'Rating'
31    COVERAGE = 'Coverage'
32    DIVERSITY = 'Diversity'
33    NOVELTY = 'Novelty'
34
35
36# Known metrics (some not supported)
37class Metric(enum.Enum):
38    """Known metrics (names)."""
39
40    # Accuracy
41    HIT_RATIO = 'HR@K'
42    NDCG = 'NDCG@K'
43    PRECISION = 'P@K'
44    RECALL = 'R@K'
45    MRR = 'MRR'
46
47    # Coverage
48    ITEM_COVERAGE = 'Item Coverage'
49    USER_COVERAGE = 'User Coverage'
50
51    # Diversity
52    GINI = 'Gini Index'
53    INTRA_LIST_SIMILARITY = 'Intra-List Similarity'
54    SIMILARITY_COS = 'Similarity Cosine'
55    SIMILARITY_EUCLID = 'Similarity Euclidean'
56
57    # Rating
58    RMSE = 'RMSE'
59    MAE = 'MAE'
60    MAPE = 'MAPE'
61    MSE = 'MSE'