diff --git a/bilder/evaluation/recall.png b/bilder/evaluation/recall.png
new file mode 100644
index 0000000000000000000000000000000000000000..4ad6386ef6dd0be8f74aa099bed2b1516d49d31a
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diff --git a/src/group_evaluation/create_combined_dataframe_with_metrics_and_plot.ipynb b/src/group_evaluation/create_combined_dataframe_with_metrics_and_plot.ipynb
index e044f4338385605f475d812cc0c7513a7b7a9373..6b3894edcd679026801cf3ed6f809e4eb4914211 100644
--- a/src/group_evaluation/create_combined_dataframe_with_metrics_and_plot.ipynb
+++ b/src/group_evaluation/create_combined_dataframe_with_metrics_and_plot.ipynb
@@ -2,7 +2,7 @@
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],
"y0": " ",
"yaxis": "y"
@@ -9926,7 +9926,7 @@
}
},
"title": {
- "text": "Vergleich der Performanz der Modelle anhand VUS-PR",
+ "text": "Vergleich der Performanz der Modelle anhand Recall",
"x": 0.5,
"xanchor": "center",
"y": 0.94,
@@ -9936,16 +9936,16 @@
"xaxis": {
"anchor": "y",
"categoryarray": [
+ "Sub-LOF",
"KMeansAD_U",
+ "Sub_KNN",
"POLY",
- "Sub-LOF",
"PCA",
- "Sub_KNN",
+ "CNN",
"OmniAnomaly",
"USAD",
- "CNN",
- "IForest",
"LSTMAD",
+ "IForest",
"LOF"
],
"categoryorder": "array",
@@ -9966,7 +9966,7 @@
1
],
"title": {
- "text": "VUS-PR"
+ "text": "Recall"
}
}
}
@@ -9977,7 +9977,7 @@
}
],
"source": [
- "metric = 'VUS-PR'\n",
+ "metric = 'Recall'#'VUS-PR'\n",
"#sort by average values\n",
"mean_sorted = df.groupby(\"Model\")[metric].mean().sort_values(ascending=False).index\n",
"\n",
@@ -10018,7 +10018,7 @@
},
{
"cell_type": "code",
- "execution_count": 41,
+ "execution_count": 9,
"metadata": {},
"outputs": [
{
@@ -10044,6 +10044,7 @@
"legendgroup": "LOF",
"marker": {
"color": "darksalmon",
+ "opacity": 0.8,
"pattern": {
"shape": ""
}
@@ -10069,6 +10070,7 @@
"legendgroup": "CNN",
"marker": {
"color": "steelblue",
+ "opacity": 0.8,
"pattern": {
"shape": ""
}
@@ -10094,6 +10096,7 @@
"legendgroup": "USAD",
"marker": {
"color": "mediumpurple",
+ "opacity": 0.8,
"pattern": {
"shape": ""
}
@@ -10119,6 +10122,7 @@
"legendgroup": "POLY",
"marker": {
"color": "lightskyblue",
+ "opacity": 0.8,
"pattern": {
"shape": ""
}
@@ -10144,6 +10148,7 @@
"legendgroup": "OmniAnomaly",
"marker": {
"color": "slateblue",
+ "opacity": 0.8,
"pattern": {
"shape": ""
}
@@ -10169,6 +10174,7 @@
"legendgroup": "IForest",
"marker": {
"color": "darkmagenta",
+ "opacity": 0.8,
"pattern": {
"shape": ""
}
@@ -10194,6 +10200,7 @@
"legendgroup": "LSTMAD",
"marker": {
"color": "blueviolet",
+ "opacity": 0.8,
"pattern": {
"shape": ""
}
@@ -10219,6 +10226,7 @@
"legendgroup": "PCA",
"marker": {
"color": "yellowgreen",
+ "opacity": 0.8,
"pattern": {
"shape": ""
}
@@ -10244,6 +10252,7 @@
"legendgroup": "Sub-LOF",
"marker": {
"color": "dodgerblue",
+ "opacity": 0.8,
"pattern": {
"shape": ""
}
@@ -10269,6 +10278,7 @@
"legendgroup": "KMeansAD_U",
"marker": {
"color": "darkseagreen",
+ "opacity": 0.8,
"pattern": {
"shape": ""
}
@@ -10294,6 +10304,7 @@
"legendgroup": "Sub_KNN",
"marker": {
"color": "firebrick",
+ "opacity": 0.8,
"pattern": {
"shape": ""
}
@@ -10959,7 +10970,7 @@
"df_mean = df.groupby(\"Model\",as_index=False)[\"duration\"].mean()\n",
"mean_sorted = df_mean.sort_values(ascending=True, by='duration')['Model']\n",
"\n",
- "fig = px.bar(df_mean, x='Model', y=duration, color='Model', category_orders={'Model':mean_sorted}, color_discrete_map=colors)\n",
+ "fig = px.bar(df_mean, x='Model', y=duration, color='Model', category_orders={'Model':mean_sorted}, color_discrete_map=colors,opacity=0.8)\n",
"fig.update_layout( legend=dict(\n",
" x=0.02,\n",
" y=-0.1,\n",