Commit dcea5f16 authored by Avzgui's avatar Avzgui
Browse files

add boxplots to experiments

parent a17a6b65
......@@ -2,12 +2,12 @@
title: "Transparency vs Performances"
output:
html_document:
toc: true
code_folding: "hide"
toc: true
code_folding: "hide"
bibliography: bibliography.bib
---
```{r include=FALSE}
```{r setup, include=FALSE}
library(ggplot2)
```
......@@ -69,8 +69,40 @@ ggtitle("Hamming loss of multi-label classifier systems by dataset") +
theme(plot.title = element_text(size=14, face="bold", hjust=0.5))
```
```{r hammingLossBox}
ggplot(
results,
aes(
x=Dataset,
y=Hamming_Loss
)
) +
geom_boxplot() +
geom_jitter(shape=16, position=position_jitter(0.1), aes(colour=Learner)) +
ylim(0.0,1.0) +
ggtitle("Hamming loss of multi-label classifier systems by dataset") +
theme(plot.title = element_text(size=14, face="bold", hjust=0.5))
```
```{r hammingLossLearnerBox}
ggplot(
results,
aes(
x=Learner,
y=Hamming_Loss
)
) +
geom_boxplot() +
geom_jitter(shape=16, position=position_jitter(0.1), aes(colour=Dataset)) +
ylim(0.0,1.0) +
ggtitle("Hamming loss of multi-label classifier systems by dataset") +
theme(plot.title = element_text(size=14, face="bold", hjust=0.5))
```
## Precision
### Micro-averaged
```{r microPrecision}
ggplot(
results,
......@@ -98,6 +130,38 @@ ggtitle("Micro-averaged precision of multi-label classifier systems by dataset")
theme(plot.title = element_text(size=14, face="bold", hjust=0.5))
```
```{r microPrecisionBox}
ggplot(
results,
aes(
x=Dataset,
y=Micro.averaged_Precision
)
) +
geom_boxplot() +
geom_jitter(shape=16, position=position_jitter(0.1), aes(colour=Learner)) +
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 microPrecisionLearnerBox}
ggplot(
results,
aes(
x=Learner,
y=Micro.averaged_Precision
)
) +
geom_boxplot() +
geom_jitter(shape=16, position=position_jitter(0.1), aes(colour=Dataset)) +
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))
```
### Macro-averaged
```{r macroPrecision}
ggplot(
results,
......@@ -125,8 +189,39 @@ ggtitle("Macro-averaged precision of multi-label classifier systems by dataset")
theme(plot.title = element_text(size=14, face="bold", hjust=0.5))
```
```{r macroPrecisionBox}
ggplot(
results,
aes(
x=Dataset,
y=Macro.averaged_Precision
)
) +
geom_boxplot() +
geom_jitter(shape=16, position=position_jitter(0.1), aes(colour=Learner)) +
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))
```
```{r macroPrecisionLearnerBox}
ggplot(
results,
aes(
x=Learner,
y=Macro.averaged_Precision
)
) +
geom_boxplot() +
geom_jitter(shape=16, position=position_jitter(0.1), aes(colour=Dataset)) +
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
### Micro-averaged
```{r microRecall}
ggplot(
......@@ -155,6 +250,38 @@ ggtitle("Micro-averaged recall of multi-label classifier systems by dataset") +
theme(plot.title = element_text(size=14, face="bold", hjust=0.5))
```
```{r microRecallBox}
ggplot(
results,
aes(
x=Dataset,
y=Micro.averaged_Recall
)
) +
geom_boxplot() +
geom_jitter(shape=16, position=position_jitter(0.1), aes(colour=Learner)) +
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 microRecallLearnerBox}
ggplot(
results,
aes(
x=Learner,
y=Micro.averaged_Recall
)
) +
geom_boxplot() +
geom_jitter(shape=16, position=position_jitter(0.1), aes(colour=Dataset)) +
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))
```
### Macro-averaged
```{r macroRecall}
ggplot(
results,
......@@ -182,8 +309,40 @@ ggtitle("Macro-averaged recall of multi-label classifier systems by dataset") +
theme(plot.title = element_text(size=14, face="bold", hjust=0.5))
```
```{r macroRecallBox}
ggplot(
results,
aes(
x=Dataset,
y=Macro.averaged_Recall
)
) +
geom_boxplot() +
geom_jitter(shape=16, position=position_jitter(0.1), aes(colour=Learner)) +
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))
```
```{r macroRecallLearnerBox}
ggplot(
results,
aes(
x=Learner,
y=Macro.averaged_Recall
)
) +
geom_boxplot() +
geom_jitter(shape=16, position=position_jitter(0.1), aes(colour=Dataset)) +
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
### Micro-averaged
```{r microFMeasure}
ggplot(
results,
......@@ -211,6 +370,38 @@ 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 microFBox}
ggplot(
results,
aes(
x=Dataset,
y=Micro.averaged_F.Measure
)
) +
geom_boxplot() +
geom_jitter(shape=16, position=position_jitter(0.1), aes(colour=Learner)) +
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 microFLearnerBox}
ggplot(
results,
aes(
x=Learner,
y=Micro.averaged_F.Measure
)
) +
geom_boxplot() +
geom_jitter(shape=16, position=position_jitter(0.1), aes(colour=Dataset)) +
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))
```
### Macro-averaged
```{r macroFMeasure}
ggplot(
results,
......@@ -238,5 +429,35 @@ ggtitle("Macro-averaged F-Measure of multi-label classifier systems by dataset")
theme(plot.title = element_text(size=14, face="bold", hjust=0.5))
```
```{r macroFBox}
ggplot(
results,
aes(
x=Dataset,
y=Macro.averaged_F.Measure
)
) +
geom_boxplot() +
geom_jitter(shape=16, position=position_jitter(0.1), aes(colour=Learner)) +
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))
```
```{r macroFLearnerBox}
ggplot(
results,
aes(
x=Learner,
y=Macro.averaged_F.Measure
)
) +
geom_boxplot() +
geom_jitter(shape=16, position=position_jitter(0.1), aes(colour=Dataset)) +
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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