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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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HANSEN: Spoken Text Authorship Analysis
HANSEN encom- passes meticulous curation of existing speech datasets accompanied by transcripts, along- side the creation of novel AI-generated spo- ken text datasets.... -
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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Minimizing Hitting Time between Disparate Groups with Shortcut Edges
Experiments on real-world datasets to evaluate the effectiveness of the algorithms proposed in paper...-
Github
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Github
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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...
