Files

DSF Random Forest
FeatureGenerators
InferenceComparison
SizeComparison
SubtreeSelection
arch-forest
forests
1 Data Conversion.ipynb
2 Initial Rooted Frequent Subtree Mining -- With Split Values.ipynb
2 Initial Rooted Frequent Subtree Mining.ipynb
2 Initial Undirected Frequent Subtree Mining.ipynb
2a Results for Frequent Rooted Subtrees - With Split Values.ipynb
2a Results for Frequent Rooted Subtrees.ipynb
2a Results for Undirected Frequent Trees.ipynb
3 Compute and Store all Embeddings of the Frequent Rooted Subtrees up to Size 6.ipynb
4 Frequent Pattern Weighting -- Which frequent subtrees should we replace by function calls?.ipynb
DSF_RF.ipynb
DSF_Samples.ipynb
ForestSampling.ipynb
InferenceComparison.ipynb
JsonToPatterns.ipynb
LearningAlgo.ipynb
README.md
SamplesSize.ipynb
Size_Comparison.ipynb
cstring
json2graphNoLeafEdges.py
json2graphNoLeafEdgesWithSplitValues.py
json2graphWithLeafEdges.py
json2graphWithLeafEdgesWithSplitValues.py
lwg
lwgr

README.md

DecisionSnippetFeatures

Code and data accompanying the paper

Pascal Welke, Fouad Alkhoury, Christian Bauckhage, and Stefan Wrobel: Decision Snippet Features. 25th International Conference on Pattern Recognition (ICPR) 2021, Milano, Italy

If you use this code, please cite our paper.