Alternatives to statistical decision trees in regulatory (eco-)toxicological bioassays
Sign Up to like & getrecommendations! Published in 2020 at "Archives of Toxicology"
DOI: 10.1007/s00204-020-02690-w
Abstract: The goal of (eco-) toxicological testing is to experimentally establish a dose or concentration–response and to identify a threshold with a biologically relevant and probably non-random deviation from “normal”. Statistical tests aid this process. Most statistical… read more here.
Keywords: alternatives statistical; toxicological bioassays; eco toxicological; statistical decision ... See more keywords
Using refined kano model and decision trees to discover learners’ needs for teaching videos
Sign Up to like & getrecommendations! Published in 2022 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-021-11744-9
Abstract: With the advancement of technology and the spread of the COVID19 epidemic, learning can no longer only be done through face-to-face teaching. Numerous digital learning materials have appeared in large numbers, changing people’s learning mode.… read more here.
Keywords: refined kano; learners needs; teaching videos; discover learners ... See more keywords
End-to-End Learning of Decision Trees and Forests
Sign Up to like & getrecommendations! Published in 2019 at "International Journal of Computer Vision"
DOI: 10.1007/s11263-019-01237-6
Abstract: Conventional decision trees have a number of favorable properties, including a small computational footprint, interpretability, and the ability to learn from little training data. However, they lack a key quality that has helped fuel the… read more here.
Keywords: decision; trees forests; end learning; decision trees ... See more keywords
Visualizing surrogate decision trees of convolutional neural networks
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Visualization"
DOI: 10.1007/s12650-019-00607-z
Abstract: Abstract Interpreting the decision-making of black boxes in machine learning becomes urgent nowadays due to their lack of transparency. One effective way to interpret these models is to transform them into interpretable surrogate models such… read more here.
Keywords: decision; neural networks; black boxes; surrogate decision ... See more keywords
Achieving Fairness with Decision Trees: An Adversarial Approach
Sign Up to like & getrecommendations! Published in 2020 at "Data Science and Engineering"
DOI: 10.1007/s41019-020-00124-2
Abstract: Fair classification has become an important topic in machine learning research. While most bias mitigation strategies focus on neural networks, we noticed a lack of work on fair classifiers based on decision trees even though… read more here.
Keywords: decision trees; tree boosting; gradient tree; approach ... See more keywords
Attribute selection for decision tree learning with class constraint
Sign Up to like & getrecommendations! Published in 2017 at "Chemometrics and Intelligent Laboratory Systems"
DOI: 10.1016/j.chemolab.2017.02.004
Abstract: Abstract Decision trees are highly favoured classifiers because of the resemblance of their understandable nature to the branched process of human thinking. But the comprehensible rationality of these trees can be severely affected by the… read more here.
Keywords: decision; attribute selection; selection; class constraint ... See more keywords
Decision trees for implementing rapid manufacturing for mass customisation
Sign Up to like & getrecommendations! Published in 2018 at "CIRP Journal of Manufacturing Science and Technology"
DOI: 10.1016/j.cirpj.2017.12.003
Abstract: Abstract This paper aims to (1) compare implementation considerations and challenges for metal and polymer rapid manufacturing (i.e. the use of additive manufacturing technologies for final part production) for mass customisation and (2) derive decision… read more here.
Keywords: decision; mass customisation; decision trees; rapid manufacturing ... See more keywords
Examining non-linear associations between population density and waist-hip ratio: An application of gradient boosting decision trees
Sign Up to like & getrecommendations! Published in 2020 at "Cities"
DOI: 10.1016/j.cities.2020.102899
Abstract: Abstract Many studies have explored the relationship between population density and obesity, but there is no consensus, particularly in dense Chinese cities. This study applied gradient boosting decision trees to 2014 national survey data to… read more here.
Keywords: population density; gradient boosting; boosting decision; decision trees ... See more keywords
Decision trees for optimizing the minimum detectable concentration of radioxenon detectors.
Sign Up to like & getrecommendations! Published in 2021 at "Journal of environmental radioactivity"
DOI: 10.1016/j.jenvrad.2021.106542
Abstract: We present a novel application of machine learning techniques to optimize the design of a radiation detection system. A decision tree-based algorithm is described which greedily optimizes partitioning of energy depositions based on a minimum… read more here.
Keywords: decision trees; radioxenon; minimum detectable; detectable concentration ... See more keywords
On Distributed Fuzzy Decision Trees for Big Data
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Fuzzy Systems"
DOI: 10.1109/tfuzz.2016.2646746
Abstract: Fuzzy decision trees (FDTs) have shown to be an effective solution in the framework of fuzzy classification. The approaches proposed so far to FDT learning, however, have generally neglected time and space requirements. In this… read more here.
Keywords: decision; fuzzy decision; scheme; fdt learning ... See more keywords
PriVDT: An Efficient Two-Party Cryptographic Framework for Vertical Decision Trees
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Information Forensics and Security"
DOI: 10.1109/tifs.2022.3231784
Abstract: Privacy-preserving decision trees (DTs) in vertical federated learning are one of the most effective tools to facilitate various privacy-critical applications in reality. However, the main bottleneck of current solutions is their huge overhead, mainly due… read more here.
Keywords: efficient two; decision trees; framework; monospace privdt ... See more keywords