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Found 8 papers, 5 papers with code
Measuring Perceived Trust in XAI-Assisted Decision-Making by Eliciting a Mental Model
In order to evaluate the impact of interpretations on perceived trust, explanation satisfaction attributes are rated by MEs through a survey.
Measuring Implicit Bias Using SHAP Feature Importance and Fuzzy Cognitive Maps
In this paper, we integrate the concepts of feature importance with implicit bias in the context of pattern classification.
Which is the best model for my data?
In this paper, we tackle the problem of selecting the optimal model for a given structured pattern classification dataset.
Forward Composition Propagation for Explainable Neural Reasoning
In the proposed FCP algorithm, each neuron is described by a composition vector indicating the role of each problem feature in that neuron.
Modeling Implicit Bias with Fuzzy Cognitive Maps
This paper presents a Fuzzy Cognitive Map model to quantify implicit bias in structured datasets where features can be numeric or discrete.
Recurrence-Aware Long-Term Cognitive Network for Explainable Pattern Classification
Besides, we propose a recurrence-aware decision model that evades the issues posed by the unique fixed point while introducing a deterministic learning algorithm to compute the tunable parameters.
Long Short-term Cognitive Networks
In this paper, we present a recurrent neural system named Long Short-term Cognitive Networks (LSTCNs) as a generalization of the Short-term Cognitive Network (STCN) model.
An interpretable semi-supervised classifier using two different strategies for amended self-labeling
In the context of some machine learning applications, obtaining data instances is a relatively easy process but labeling them could become quite expensive or tedious.
