grogv3 / grog-cubi

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Jean-Francois Leveque
3aa413f5 1 parent 624e8624

Correction calcul précision et rappel

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Showing 1 changed file with 25 additions and 5 deletions
...@@ -16,12 +16,14 @@ public class PostprocessingExpert { ...@@ -16,12 +16,14 @@ public class PostprocessingExpert {
16 Set<Long> sampleItemIds; 16 Set<Long> sampleItemIds;
17 Set<Long> recommendedItemIds; 17 Set<Long> recommendedItemIds;
18 Set<Long> sampleUserIds; 18 Set<Long> sampleUserIds;
19 + Set<Long> annotatedUserIds;
19 Map<Long, Set<Long>> sampleItemUserIds; 20 Map<Long, Set<Long>> sampleItemUserIds;
20 Map<Long, Integer> itemRecommandationUserCounts; 21 Map<Long, Integer> itemRecommandationUserCounts;
21 int recommendableItemCount; 22 int recommendableItemCount;
22 int recommendedItemCount; 23 int recommendedItemCount;
23 int recommendableItemUserCount; 24 int recommendableItemUserCount;
24 int annotatedItemUserCount; 25 int annotatedItemUserCount;
26 + int recommendedItemAnnotatedUserCount;
25 int recommendedItemUserCount; 27 int recommendedItemUserCount;
26 int validRecommendationCount; 28 int validRecommendationCount;
27 double itemRecommandationUserCountRelativeStdDeviation; 29 double itemRecommandationUserCountRelativeStdDeviation;
...@@ -36,6 +38,7 @@ public class PostprocessingExpert { ...@@ -36,6 +38,7 @@ public class PostprocessingExpert {
36 38
37 public void analyze() { 39 public void analyze() {
38 analyzeSample(); 40 analyzeSample();
41 + analyzeAnnotated();
39 analyzeRecommendations(); 42 analyzeRecommendations();
40 } 43 }
41 44
...@@ -51,6 +54,19 @@ public class PostprocessingExpert { ...@@ -51,6 +54,19 @@ public class PostprocessingExpert {
51 return computePrecisionRecall(); 54 return computePrecisionRecall();
52 } 55 }
53 56
57 + protected void analyzeAnnotated() {
58 +
59 + annotatedUserIds = new HashSet<>();
60 +
61 + for (PostprocessingSample sample : annotatedList) {
62 + Long userId = sample.getUserId();
63 + annotatedUserIds.add(userId);
64 + }
65 +
66 + annotatedItemUserCount = annotatedList.size();
67 + logger.debug("PR: Nombre d'associations annotées {}", annotatedItemUserCount);
68 + }
69 +
54 protected void analyzeSample() { 70 protected void analyzeSample() {
55 71
56 sampleItemIds = new HashSet<>(); 72 sampleItemIds = new HashSet<>();
...@@ -90,8 +106,10 @@ public class PostprocessingExpert { ...@@ -90,8 +106,10 @@ public class PostprocessingExpert {
90 protected void analyzeRecommendations() { 106 protected void analyzeRecommendations() {
91 recommendedItemUserCount = 0; 107 recommendedItemUserCount = 0;
92 validRecommendationCount = 0; 108 validRecommendationCount = 0;
109 + recommendedItemAnnotatedUserCount = 0;
93 recommendedItemIds = new HashSet<>(); 110 recommendedItemIds = new HashSet<>();
94 itemRecommandationUserCounts = new HashMap<>(); 111 itemRecommandationUserCounts = new HashMap<>();
112 +
95 for (PostprocessingSample annote : annotatedList) { 113 for (PostprocessingSample annote : annotatedList) {
96 logger.trace("Annotated item {}, user {}", annote.getItemId(), annote.getUserId()); 114 logger.trace("Annotated item {}, user {}", annote.getItemId(), annote.getUserId());
97 } 115 }
...@@ -114,16 +132,18 @@ public class PostprocessingExpert { ...@@ -114,16 +132,18 @@ public class PostprocessingExpert {
114 } 132 }
115 } 133 }
116 logger.trace("Recommendation item {}, user {}", reco.getItemId(), reco.getUserId()); 134 logger.trace("Recommendation item {}, user {}", reco.getItemId(), reco.getUserId());
135 + if (annotatedUserIds.contains(userId)) {
136 + recommendedItemAnnotatedUserCount++;
137 + }
117 if (annotatedList.contains(reco)) { 138 if (annotatedList.contains(reco)) {
118 validRecommendationCount++; 139 validRecommendationCount++;
119 } 140 }
120 } 141 }
121 recommendedItemCount = recommendedItemIds.size(); 142 recommendedItemCount = recommendedItemIds.size();
122 logger.debug("C: Nombre d'objets recommandés {}", recommendedItemCount); 143 logger.debug("C: Nombre d'objets recommandés {}", recommendedItemCount);
123 - logger.debug("C/PR: Nombre de couples item-user recommandés {}", recommendedItemUserCount); 144 + logger.debug("C: Nombre de couples item-user recommandés {}", recommendedItemUserCount);
124 - annotatedItemUserCount = annotatedList.size();
125 - logger.debug("PR: Nombre d'associations annotées {}", annotatedItemUserCount);
126 logger.debug("PR: Nombre de recommandations annotées {}", validRecommendationCount); 145 logger.debug("PR: Nombre de recommandations annotées {}", validRecommendationCount);
146 + logger.debug("PR: Nombre de couples item-user recommandés pour les users annotés {}", recommendedItemAnnotatedUserCount);
127 } 147 }
128 148
129 protected PostprocessingStatistics computeStatistics() { 149 protected PostprocessingStatistics computeStatistics() {
...@@ -169,8 +189,8 @@ public class PostprocessingExpert { ...@@ -169,8 +189,8 @@ public class PostprocessingExpert {
169 float recall; 189 float recall;
170 190
171 logger.debug("PR: nombre de recommandations annotées {}", validRecommendationCount); 191 logger.debug("PR: nombre de recommandations annotées {}", validRecommendationCount);
172 - logger.debug("PR: nombre de recommandations {}", recommendedItemUserCount); 192 + logger.debug("PR: nombre de recommandations pour utilisateurs annotés {}", recommendedItemAnnotatedUserCount);
173 - precision = (float) validRecommendationCount / recommendedItemUserCount; 193 + precision = (float) validRecommendationCount / recommendedItemAnnotatedUserCount;
174 logger.debug("PR: précision {}", String.format(Locale.FRENCH, "%.3f", precision)); 194 logger.debug("PR: précision {}", String.format(Locale.FRENCH, "%.3f", precision));
175 logger.debug("PR: nombre d'associations annotées {}", annotatedItemUserCount); 195 logger.debug("PR: nombre d'associations annotées {}", annotatedItemUserCount);
176 recall = (float) validRecommendationCount / annotatedItemUserCount; 196 recall = (float) validRecommendationCount / annotatedItemUserCount;
......