Commit c47706c3 authored by Antoine RICHARD's avatar Antoine RICHARD
Browse files

add principal performance measures

parent 6b31a8f4
......@@ -157,7 +157,7 @@ public class App
// Init Learners
HashMap<String, MultiLabelLearnerBase> learners = new HashMap<>();
//learners.put("FuzzyBayes", new FuzzyBayes());
learners.put("FuzzyBayes", new FuzzyBayes());
learners.put("HistBayes", new HistBayes());
//learners.put("MLkNN", new MLkNN()); // k-Nearest Neighboors
//learners.put("BPMLL", new BPMLL());
......@@ -166,7 +166,7 @@ public class App
//learners.put("RAkEL+LMT", new RAkEL(new LabelPowerset(new LMT()))); // Decision Tree
//learners.put("RAkEL+Ripper", new RAkEL(new LabelPowerset(new JRip()))); // Rules
//learners.put("RAkEL+PART", new RAkEL(new LabelPowerset(new PART()))); // DT + Rules
//learners.put("RAkEL+NaiveBayes", new RAkEL(new LabelPowerset(new NaiveBayes()))); // Bayes Net
learners.put("RAkEL+NaiveBayes", new RAkEL(new LabelPowerset(new NaiveBayes()))); // Bayes Net
//learners.put("RAkEL+KStar", new RAkEL(new LabelPowerset(new KStar()))); // instance based
//learners.put("RAkEL+SMO", new RAkEL(new LabelPowerset(new SMO()))); // SVM
......
......@@ -69,5 +69,174 @@ ggtitle("Hamming loss of multi-label classifier systems by dataset") +
theme(plot.title = element_text(size=14, face="bold", hjust=0.5))
```
## Precision
```{r microPrecision}
ggplot(
results,
aes(
x=Dataset,
y=Micro.averaged_Precision,
fill=Learner
)
) +
geom_bar(
stat = "identity",
color = "black",
position = position_dodge()
) +
geom_errorbar(
aes(
ymin=Micro.averaged_Precision - Micro.averaged_Precision_std,
ymax=Micro.averaged_Precision + Micro.averaged_Precision_std
),
width=.2,
position = position_dodge(.9)
) +
ylim(0.0,1.0) +
ggtitle("Micro-averaged precision of multi-label classifier systems by dataset") +
theme(plot.title = element_text(size=14, face="bold", hjust=0.5))
```
```{r macroPrecision}
ggplot(
results,
aes(
x=Dataset,
y=Macro.averaged_Precision,
fill=Learner
)
) +
geom_bar(
stat = "identity",
color = "black",
position = position_dodge()
) +
geom_errorbar(
aes(
ymin=Macro.averaged_Precision - Macro.averaged_Precision_std,
ymax=Macro.averaged_Precision + Macro.averaged_Precision_std
),
width=.2,
position = position_dodge(.9)
) +
ylim(0.0,1.0) +
ggtitle("Macro-averaged precision of multi-label classifier systems by dataset") +
theme(plot.title = element_text(size=14, face="bold", hjust=0.5))
```
## Recall
```{r microRecall}
ggplot(
results,
aes(
x=Dataset,
y=Micro.averaged_Recall,
fill=Learner
)
) +
geom_bar(
stat = "identity",
color = "black",
position = position_dodge()
) +
geom_errorbar(
aes(
ymin=Micro.averaged_Recall - Micro.averaged_Recall_std,
ymax=Micro.averaged_Recall + Micro.averaged_Recall_std
),
width=.2,
position = position_dodge(.9)
) +
ylim(0.0,1.0) +
ggtitle("Micro-averaged recall of multi-label classifier systems by dataset") +
theme(plot.title = element_text(size=14, face="bold", hjust=0.5))
```
```{r macroRecall}
ggplot(
results,
aes(
x=Dataset,
y=Macro.averaged_Recall,
fill=Learner
)
) +
geom_bar(
stat = "identity",
color = "black",
position = position_dodge()
) +
geom_errorbar(
aes(
ymin=Macro.averaged_Recall - Macro.averaged_Recall_std,
ymax=Macro.averaged_Recall + Macro.averaged_Recall_std
),
width=.2,
position = position_dodge(.9)
) +
ylim(0.0,1.0) +
ggtitle("Macro-averaged recall of multi-label classifier systems by dataset") +
theme(plot.title = element_text(size=14, face="bold", hjust=0.5))
```
## F-Measure
```{r microFMeasure}
ggplot(
results,
aes(
x=Dataset,
y=Micro.averaged_F.Measure,
fill=Learner
)
) +
geom_bar(
stat = "identity",
color = "black",
position = position_dodge()
) +
geom_errorbar(
aes(
ymin=Micro.averaged_F.Measure - Micro.averaged_F.Measure_std,
ymax=Micro.averaged_F.Measure + Micro.averaged_F.Measure_std
),
width=.2,
position = position_dodge(.9)
) +
ylim(0.0,1.0) +
ggtitle("Micro-averaged F-Measure of multi-label classifier systems by dataset") +
theme(plot.title = element_text(size=14, face="bold", hjust=0.5))
```
```{r macroFMeasure}
ggplot(
results,
aes(
x=Dataset,
y=Macro.averaged_F.Measure,
fill=Learner
)
) +
geom_bar(
stat = "identity",
color = "black",
position = position_dodge()
) +
geom_errorbar(
aes(
ymin=Macro.averaged_F.Measure - Macro.averaged_F.Measure_std,
ymax=Macro.averaged_F.Measure + Macro.averaged_F.Measure_std
),
width=.2,
position = position_dodge(.9)
) +
ylim(0.0,1.0) +
ggtitle("Macro-averaged F-Measure of multi-label classifier systems by dataset") +
theme(plot.title = element_text(size=14, face="bold", hjust=0.5))
```
# References
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