Recent advances and applications of machine learning in solid-state materials science

J Schmidt, MRG Marques, S Botti… - npj computational …, 2019 - nature.com
One of the most exciting tools that have entered the material science toolbox in recent years
is machine learning. This collection of statistical methods has already proved to be capable …

Machine behaviour

I Rahwan, M Cebrian, N Obradovich, J Bongard… - Nature, 2019 - nature.com
Abstract Machines powered by artificial intelligence increasingly mediate our social, cultural,
economic and political interactions. Understanding the behaviour of artificial intelligence …

[HTML][HTML] A comparison of machine learning algorithms for diabetes prediction

JJ Khanam, SY Foo - Ict Express, 2021 - Elsevier
Diabetes is a disease that has no permanent cure; hence early detection is required. Data
mining, machine learning (ML) algorithms, and Neural Network (NN) methods are used in …

Definitions, methods, and applications in interpretable machine learning

WJ Murdoch, C Singh, K Kumbier… - Proceedings of the …, 2019 - National Acad Sciences
Machine-learning models have demonstrated great success in learning complex patterns
that enable them to make predictions about unobserved data. In addition to using models for …

Interpretable machine learning: definitions, methods, and applications

WJ Murdoch, C Singh, K Kumbier, R Abbasi-Asl… - arxiv preprint arxiv …, 2019 - arxiv.org
Machine-learning models have demonstrated great success in learning complex patterns
that enable them to make predictions about unobserved data. In addition to using models for …

Machine learning in banking risk management: A literature review

M Leo, S Sharma, K Maddulety - Risks, 2019 - mdpi.com
There is an increasing influence of machine learning in business applications, with many
solutions already implemented and many more being explored. Since the global financial …

Measuring algorithmically infused societies

C Wagner, M Strohmaier, A Olteanu, E Kıcıman… - Nature, 2021 - nature.com
It has been the historic responsibility of the social sciences to investigate human societies.
Fulfilling this responsibility requires social theories, measurement models and social data …

Deep learning approach for diabetes prediction using PIMA Indian dataset

H Naz, S Ahuja - Journal of Diabetes & Metabolic Disorders, 2020 - Springer
Abstract Purpose International Diabetes Federation (IDF) stated that 382 million people are
living with diabetes worldwide. Over the last few years, the impact of diabetes has been …

A boosted decision tree approach using Bayesian hyper-parameter optimization for credit scoring

Y **a, C Liu, YY Li, N Liu - Expert systems with applications, 2017 - Elsevier
Credit scoring is an effective tool for banks to properly guide decision profitably on granting
loans. Ensemble methods, which according to their structures can be divided into parallel …

Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research

S Lessmann, B Baesens, HV Seow… - European Journal of …, 2015 - Elsevier
Many years have passed since Baesens et al. published their benchmarking study of
classification algorithms in credit scoring [Baesens, B., Van Gestel, T., Viaene, S …