Results 81 to 90 of about 66,762 (195)

Psychology Meets Machine Learning: Interdisciplinary Perspectives on Algorithmic Job Candidate Screening

, 2018
In a rapidly digitizing world, machine learning algorithms are increasingly employed in scenarios that directly impact humans. This also is seen in job candidate screening. Data-driven candidate assessment is gaining interest, due to high scalability and
König, Cornelis J. (author), Born, Marise Ph. (author), Achmadnoer Sukma Wicaksana, Sukma (author), Liem, C.C.S. (author), Demetriou, A.M. (author), Langer, Markus (author), Hiemstra, Annemarie M.F. (author)   +6 more
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A Lightweight and Explainable Machine Learning Framework for Cervical Cancer Risk Prediction [PDF]

ITM Web of Conferences
Cervical cancer is a global health issue of serious concern especially in the low resource areas where access to good screening facilities is a hindrance.
Biswas Mithun, Chaudhuri Avijit Kumar, Chaudhari Sushmita, Shome Subhankar   +3 more
doaj   +1 more source

Model-Agnostic Interpretability of Machine Learning

CoRR, 2016
Understanding why machine learning models behave the way they do empowers both system designers and end-users in many ways: in model selection, feature engineering, in order to trust and act upon the predictions, and in more intuitive user interfaces.
Marco Túlio Ribeiro, Sameer Singh 0001, Carlos Guestrin   +2 more
openaire   +2 more sources

Alternating model trees

, 2015
Model tree induction is a popular method for tackling regression problems requiring interpretable models. Model trees are decision trees with multiple linear regression models at the leaf nodes.
Kramer, Stefan, Eibe Frank, Michael Mayo, Mayo, Michael, Frank, Eibe, Stefan Kramer   +5 more
core   +1 more source

Learning Interpretable Representations of Images

, 2019
Computers represent images with pixels and each pixel contains three numbers for red, green and blue colour values. These numbers are meaningless for humans and they are mostly useless when used directly with classical machine learning techniques like ...
Szabo, Attila
core  

An interpretable machine learning approach for predicting high-frequency hearing loss risk in occupational workers

The Egyptian Journal of Otolaryngology
Background High-frequency hearing loss (HFHL) is prevalent among noise-exposed workers, yet routine screening remains costly. This study develops and validates an interpretable machine learning model for predicting HFHL risk, aiming to provide a cost ...
Kai Wen, Xu Liao, Lingyan Yuan, Jinqiong Chen, Yingli Liu, Yanbing Leng   +5 more
doaj   +1 more source

Interpretable machine learning study of a collector based on combined twisted-tape and wavy-tape inserts

Case Studies in Thermal Engineering
Nowadays, the efficiency of air collectors for solar thermal applications is still low, and many researchers tend to use machine learning to predict and model the performance of thermal systems, but most of the existing machine learning methods are ...
Bingbin Ge, Dianwei Qi, Jinggong Zhou, Neng Qian, Li Zhang   +4 more
doaj   +1 more source

Analytic field solution for machine learning integrating physics model and data driven approach

AIP Advances
We derive analytical formulas for machine learning that merge a physics model with a data driven approach. We use a path integral method to find a field solution that calculates machine learning statistics while considering the physics model’s ...
Xiaobin Wang, April Wang
doaj   +1 more source

Interpretable machine learning algorithms reveal gut microbiome features associated with atopic dermatitis

Frontiers in Immunology
BackgroundThe “gut–skin axis” has been proposed to play an important role in the development and symptoms of atopic dermatitis. Therefore, we have constructed an interpretable machine learning framework to quantitatively screen key gut flora.MethodsThe ...
Jingtai Ma, Jingtai Ma, Yiting Fang, Yiting Fang, Shiqi Li, Shiqi Li, Lilian Zeng, Siyi Chen, Zhifeng Li, Guiyuan Ji, Xingfen Yang, Wei Wu, Wei Wu   +12 more
doaj   +1 more source

Nature of ‎Metal-Support Interaction Discovered by Interpretable Machine ‎Learning

Metal catalysts supported on oxides play a paramount role in numerous industrial reactions. ‎Modulating metal-support interaction is a key strategy to boost ‎catalytic productivity and ‎stability; however, the nature of metal-support interaction and ...
Wei-Xue, Li, Tairan, Wang, Yutao, Wang, Jianyu, Hu, Runhai , Ouyang, Xuting, Chai, Wu, Shu, Sulei, Hu   +7 more
core   +1 more source