Results 71 to 80 of about 3,458,167 (137)

Contextual recommendation modeling in eCoaching with machine learning, X-AI, and semantic ontology. [PDF]

Front Digit Health
Chatterjee A, Avazov N.
europepmc   +1 more source

Assessment of reproductive performance in dairy cows using explainable machine learning. [PDF]

Arch Anim Breed
Çelik Gürbulak E, Kara U, Canooğlu E, Arslan HA, Çetin E, Demirel M, Gürbulak K.   +6 more
europepmc   +1 more source

Critical Appraisal of Artificial Intelligence for Rare-Event Recognition: Principles and Pharmacovigilance Case Studies. [PDF]

Drug Saf
Norén GN, Meldau EL, Ellenius J.
europepmc   +1 more source

Multi-metric evaluation and parametric optimization of stochastic gradient boosting machines for genomic prediction and selection in wheat (Triticum aestivum) breeding. [PDF]

G3 (Bethesda)
Munroe HN, Osatohanmwen BE, Reza Sharifi A.   +2 more
europepmc   +1 more source

Explainable AI Approaches in Federated Learning: Systematic Review. [PDF]

JMIR AI
Tunduny T, Shibwabo B.
europepmc   +1 more source

Urban environmental exposure as a factor in adaptive neuromodulation: a conceptual framework. [PDF]

Front Hum Neurosci
Qamili A, Cenameri A.
europepmc   +1 more source

Recognizing Properties of Decision Rule Systems Using Deterministic and Nondeterministic Decision Trees

Journal of Intelligent Learning Systems and Applications
Kerven Durdymyradov, Mikhail Moshkov
openaire   +2 more sources

Analyzing student performance in distance learning with genetic algorithms and decision trees. Applied Artificial Intelligence 20(8): 655-674. Page 11 of 14

, 2006
Analyzing student performance in distance learning Restore: double line spacing for normal, left and right margins at 3.17 cm, top and bottom margins at 2.54 cm Page 1 of 30 Students who enrol in the undergraduate program on informatics at the Hellenic ...
Dimitris Kalles, Decision Trees, Christos Pierrakeas   +2 more
core  

A ERSF-VIPA framework: scalable wildlife movement modelling for conflict mitigation. [PDF]

Mov Ecol
Chen X, Li J, Cao X, Yang Y, Chapman CA, Li X, Qiao R, Wang X, Yang F, Kong D.   +9 more
europepmc   +1 more source

Emerging applications of traditional and generative artificial intelligence in liver transplantation. [PDF]

Liver Transpl
Ge WH, Bishara A, Bishara A, Braun H, Simonetto DA, Ge J.   +5 more
europepmc   +1 more source