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Comprehensible classification models: a position paper
The vast majority of the literature evaluates the performance of classification models using
only the criterion of predictive accuracy. This paper reviews the case for considering also the …
only the criterion of predictive accuracy. This paper reviews the case for considering also the …
Monotonic classification: An overview on algorithms, performance measures and data sets
Currently, knowledge discovery in databases is an essential first step when identifying valid,
novel and useful patterns for decision making. There are many real-world scenarios, such as …
novel and useful patterns for decision making. There are many real-world scenarios, such as …
Data preprocessing techniques for classification without discrimination
Abstract Recently, the following Discrimination-Aware Classification Problem was
introduced: Suppose we are given training data that exhibit unlawful discrimination; eg …
introduced: Suppose we are given training data that exhibit unlawful discrimination; eg …
Improving ship energy efficiency: Models, methods, and applications
Maritime transportation is the backbone of global trade, as ships carry over 80% of trading
goods worldwide. As the ship** industry is mainly powered by heavy fuel oil, it has an …
goods worldwide. As the ship** industry is mainly powered by heavy fuel oil, it has an …
Three naive bayes approaches for discrimination-free classification
In this paper, we investigate how to modify the naive Bayes classifier in order to perform
classification that is restricted to be independent with respect to a given sensitive attribute …
classification that is restricted to be independent with respect to a given sensitive attribute …
Building classifiers with independency constraints
In this paper we study the problem of classifier learning where the input data contains
unjustified dependencies between some data attributes and the class label. Such cases …
unjustified dependencies between some data attributes and the class label. Such cases …
Discrimination aware decision tree learning
Recently, the following discrimination aware classification problem was introduced: given a
labeled dataset and an attribute B, find a classifier with high predictive accuracy that at the …
labeled dataset and an attribute B, find a classifier with high predictive accuracy that at the …
A machine learning approach to predicting academic performance in Pennsylvania's schools
Academic performance prediction is an indispensable task for policymakers. Academic
performance is frequently examined using classical statistical software, which can be used …
performance is frequently examined using classical statistical software, which can be used …
Explanations for Monotonic Classifiers.
In many classification tasks there is a requirement of monotonicity. Concretely, if all else
remains constant, increasing (resp. ádecreasing) the value of one or more features must not …
remains constant, increasing (resp. ádecreasing) the value of one or more features must not …
Ship** domain knowledge informed prediction and optimization in port state control
Maritime transportation is the backbone of global supply chain. To improve maritime safety,
protect the marine environment, and set out seafarers' rights, port state control (PSC) …
protect the marine environment, and set out seafarers' rights, port state control (PSC) …