Results 131 to 140 of about 4,859,475 (319)

Decision Trees [PDF]

ACM Inroads, 2019
Marie desJardins, Michael L. Littman, John Barr   +2 more
openaire   +3 more sources

Multi-Rules Mining Algorithm for Combinatorially Exploded Decision Trees With Modified Aitchison-Aitken Function-Based Bayesian Optimization

IEEE Open Journal of the Computer Society
Decision trees offer the benefit of easy interpretation because they allow the classification of input data based on if–then rules. However, as decision trees are constructed by an algorithm that achieves clear classification with minimum ...
Yuto Omae, Masaya Mori, Yohei Kakimoto
doaj   +1 more source

Learning optimal decision trees using constraint programming

Constraints, 2020
Hélène Verhaeghe, Siegfried Nijssen, Gilles Pesant, Claude-Guy Quimper, P. Schaus   +4 more
semanticscholar   +1 more source

Beyond the Beam: Exploring Charged Particle Nanoprinting

Advanced Functional Materials, EarlyView.
Charged particle nanoprinting using electrons and ions is highly advanced, offering great potential for research and industry. However, challenges in precursor design and process optimization persist, but also offer great opportunities to drive nanofabrication innovations.
Nicolas Paul Jochmann, Alba Salvador‐Porroche, Sven Barth   +2 more
wiley   +1 more source

Decision tree parsing using a hidden derivation model [PDF]

, 1994
F. Jelinek, John Lafferty, David M. Magerman, R. L. Mercer, Adwait Ratnaparkhi, Salim Roukos   +5 more
openalex   +1 more source

Tunable Synthetic Hydrogel Modulates Hepatic Lineage Specification of Human Liver Organoid

Advanced Functional Materials, EarlyView.
In this study, a synthetic hydrogel is reported that supports the formation of hiPSC‐derived human liver organoids (HLOs). Hepatic lineage specification can be modulated via conjugation of RGD peptide to hydrogel: RGD‐conjugated hydrogels promote cholangiocyte differentiation, whereas RGD‐free hydrogels favor hepatocyte commitment of HLO cells.
Lei Wang, Lasse Riediger, Qi Rao, Xun Xu, Yan Nie, Yiduo Zhou, Junyao Zhang, Peng Tang, Weiwei Wang, Frank Tacke, Adrien Guillot, Ludovic Vallier, Irene Talon, Wenzhong Li, Yi‐An Yang, Rainer Haag, Nan Ma   +16 more
wiley   +1 more source

Identifying relapse predictors in individual participant data with decision trees. [PDF]

BMC Psychiatry, 2023
Böttcher L, Breedvelt JJF, Warren FC, Segal Z, Kuyken W, Bockting CLH.   +5 more
europepmc   +1 more source

Learning kμ decision trees on the uniform distribution [PDF]

, 1993
Thomas R. Hancock
openalex   +1 more source

Artificial Intelligence‐Driven Development in Rechargeable Battery Materials: Progress, Challenges, and Future Perspectives

Advanced Functional Materials, EarlyView.
AI is transforming the research paradigm of battery materials and reshaping the entire landscape of battery technology. This comprehensive review summarizes the cutting‐edge applications of AI in the advancement of battery materials, underscores the critical challenges faced in harnessing the full potential of AI, and proposes strategic guidance for ...
Qingyun Hu, Junyuan Lu, Jian Hui, Ziyuan Rao, Yang Ren, Hong Wang   +5 more
wiley   +1 more source

On the integration of decision trees with mixture cure model. [PDF]

Stat Med, 2023
Aselisewine W, Pal S.
europepmc   +1 more source