Results 141 to 150 of about 744,531 (188)

Hybrid intelligent systems for liver disease prediction: a demographic-aware machine learning framework. [PDF]

Front Med (Lausanne)
Saraf E, Yang M, Sakthivel R, Zhang Y, Chokkakula S, Kong Y, Alekya V, Naveen B, Yang B.   +8 more
europepmc   +1 more source

Environmental filtering drives patterns of ant species richness and activity across Hawaiian coffee farms. [PDF]

J Insect Sci
Cowal S, Mueller M, Johnson MA.
europepmc   +1 more source

PanForest: predicting genes in genomes using random forests. [PDF]

Bioinformatics
Beavan AJS, Domingo-Sananes MR, McInerney JO.   +2 more
europepmc   +1 more source

Comparative entropy analysis of 2D transition metal tetrahydroxyquinones via machine learning approaches. [PDF]

Sci Rep
Irfan M, Bashir N, Gaid ASA, Althobaiti T, Rehman HU, Semaničová-Feňovčíková A.   +5 more
europepmc   +1 more source

Tree-based ensemble learning models for protein-protein interactions detection: a review and experimental evaluation. [PDF]

BioData Min
Taha K.
europepmc   +1 more source

Geographic authentication of <i>Amomum tsaoko</i> seeds using fourier transform-near infrared spectroscopy combined with machine learning techniques and feature reduction analysis. [PDF]

Front Plant Sci
Zheng Y, Lan S, Hu H, Huang X, Wang H, Cao H, Liu X, Yang Y, Ji S, Xie H.   +9 more
europepmc   +1 more source

Integrating biological and machine learning models for rainbow trout growth: Balancing accuracy and interpretability. [PDF]

PLoS One
Fulton L, Lyu P.
europepmc   +1 more source

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Random Trees

Oberwolfach Reports, 2009
The meeting was devoted to random trees, a central concept in mathematics that provides a key way of thinking about relationships between objects such as particles in a fluid, individuals in a population, or labels in a search algorithm. Particular emphasis was put on the role of random trees in physics, biology, and computer science.
Ellen Baake, Donald A. Dawson, Andreas Greven, Frank den Hollander   +3 more
  +5 more sources