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Debiaser for Multiple Variables (DEMV)
DEMV is a Debiaser for Multiple Variables that aims to increase Fairness in any given dataset, both binary and categorical, with one or more sensitive variables, while keeping...-
ipynb
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ipynb
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GiveMeSomeCreditSC
The GiveMeSomeCredit dataset - https://www.kaggle.com/c/GiveMeSomeCredit - contains different features of borrowers. The task is predicting the financial distress of a...-
ZIP
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ZIP
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Frank Experiments
Dataset with experimental results for the "Frank" hybrid decision-making system, with simulated users. Features: - CA. Co-evolutionary Accuracy. Accuracy reached by the user...-
JSON
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JSON
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Medical Dataset
The medical dataset contains a corpus of fully anonymized clinical text. Each document in the corpus is associated with a set of ICD-9 codes which represents the diagnosis...-
ZIP
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ZIP
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CSV
The resource: 'Churn Dataset' is not accessible as guest user. You must login to access it!
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CSV
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German Credit
In the german credit dataset each one of the 1,000 persons is classified as a good or bad creditor according to attributes like age, sex, checking_account, credit_amount,...-
CSV
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CSV
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Compas
The compas dataset contains the features used by the COMPAS algorithm for scoring defendants and their risk (Low, Medium and High), for over $4,000$ individuals. We considered...-
CSV
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CSV
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Dataset Adult
The adult dataset includes $48,842$ instances with demographic information like age, workclass, marital-status, race, capital-loss, capital-gain etc. The income attribute...-
CSV
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CSV
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Focus Metric
https://github.com/HPAI-BSC/Focus-Metric Implementation of the Focus metric. This metric is able to evaluate explainability methods and quantify their coherency to the task...-
github
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github
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Visualizing the Results of Boolean Matrix Factorizations
We provide a method to visualize the results of Boolean Matrix Factorization algorithms. Our method can also be used to visualize overlapping clusters in bipartite graphs. The... -
GLocalX - Explaining in a Local to Global setting
GLocalX is a model-agnostic Local to Global explanation algorithm. Given a set of local explanations expressed in the form of decision rules, and a black-box model to explain,... -
XAI Method for explaining time-series
LASTS is a framework that can explain the decisions of black box models for time series classification. The explanation consists of factual and counterfactual rules revealing... -
LORE
The recent years have witnessed the rise of accurate but obscure decision systems which hide the logic of their internal decision processes to the users. The lack of...-
python
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python
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MARLENA
MARLENA is novel technique able to explain the reasons behind any black-box multi-label classifier decision. It will generate an explanation in the form of a decision rule....-
python
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python
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TriplEx - Explaining with Triples
TRIPLEX is an explainability package for Transformer-based models fine-tuned on Natural Language Inference, Semantic Text Similarity, or Text Classification tasks. TRIPLEX... -
Reducing Graph Structural Bias by Adding shortcut edges
Algorithms that tackle the problem of minimizing average/maximum hitting time (BMAH/BMMH) between different social network groups, given fixed shortcut edges. The...-
Data
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Data
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Geolet
Geolet is a Python library that offers an interpretable transformation and classification approach for trajectory data. Geolet first partitions trajectories into multiple... -
Visualizing the Results of Biclustering and Boolean Matrix Factorization Algo...
This archive contains the code to visualize biclusters from the paper "Visualizing Overlapping Biclusterings and Boolean Matrix Factorizations" by Thibault Marette, Pauli... -
Interaction bias. Experiments dataset
Artificial Intelligence (AI) is increasingly used to build Decision Support Systems (DSS) across many domains. In our work, we conducted a series of experiments designed to...-
JSON
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JSON
