Subgroup Discovery
15 papers with code • 0 benchmarks • 0 datasets
Benchmarks
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Most implemented papers
Discovering outstanding subgroup lists for numeric targets using MDL
We propose a dispersion-aware problem formulation for subgroup set discovery that is based on the minimum description length (MDL) principle and subgroup lists.
Robust subgroup discovery
This novel model class allows us to formalise the problem of optimal robust subgroup discovery using the Minimum Description Length (MDL) principle, where we resort to optimal Normalised Maximum Likelihood and Bayesian encodings for nominal and numeric targets, respectively.
"What makes my queries slow?": Subgroup Discovery for SQL Workload Analysis
Among daily tasks of database administrators (DBAs), the analysis of query workloads to identify schema issues and improving performances is crucial.
Contrastive Principal Component Analysis
We present a new technique called contrastive principal component analysis (cPCA) that is designed to discover low-dimensional structure that is unique to a dataset, or enriched in one dataset relative to other data.
Unsupervised learning with contrastive latent variable models
Here, we present a probabilistic model for dimensionality reduction to discover signal that is enriched in the target dataset relative to the background dataset.
FairVis: Visual Analytics for Discovering Intersectional Bias in Machine Learning
We present FairVis, a mixed-initiative visual analytics system that integrates a novel subgroup discovery technique for users to audit the fairness of machine learning models.
Embedding-based Silhouette Community Detection
SkBlaz/SCD
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Mining complex data in the form of networks is of increasing interest in many scientific disciplines.
REDS: Rule Extraction for Discovering Scenarios
Given a computational budget, results tend to get worse as the number of inputs of the simulation model and the cost of simulations increase.
Explainable Subgraphs with Surprising Densities: A Subgroup Discovery Approach
The connectivity structure of graphs is typically related to the attributes of the nodes.
Interpretable Summaries of Black Box Incident Triaging with Subgroup Discovery
The need of predictive maintenance comes with an increasing number of incidents reported by monitoring systems and equipment/software users.
