Results 101 to 110 of about 744,531 (188)

optRF: Optimising random forest stability by determining the optimal number of trees

BMC Bioinformatics
Machine learning is frequently used to make decisions based on big data. Among these techniques, random forest is particularly prominent. Although random forest is known to have many advantages, one aspect that is often overseen is that it is a non ...
Thomas M. Lange, Mehmet Gültas, Armin O. Schmitt, Felix Heinrich   +3 more
doaj   +1 more source

Robotic Active Information Gathering for Spatial Field Reconstruction with Rapidly-Exploring Random Trees and Online Learning of Gaussian Processes. [PDF]

Sensors (Basel), 2019
Viseras A, Shutin D, Merino L.
europepmc   +1 more source

Random friend trees

We study a random recursive tree model featuring complete redirection called the random friend tree and introduced by Saramäki and Kaski. Vertices are attached in a sequential manner one by one by selecting an existing target vertex and connecting to one of its neighbours (or friends), chosen uniformly at random.
Berry, Louigi Addario, Briend, Simon, Devroye, Luc, Donderwinkel, Serte, Kerriou, Céline, Lugosi, Gábor   +5 more
openaire   +2 more sources

An Overview and Comparison of Traditional Motion Planning Based on Rapidly Exploring Random Trees. [PDF]

Sensors (Basel)
Chu Y, Chen Q, Yan X.
europepmc   +1 more source

Automated guided vehicle (AGV) path optimization method based on improved rapidly-exploring random trees. [PDF]

PeerJ Comput Sci
Ren Z, Cai A, Xu F.
europepmc   +1 more source

Vector Encoding of Phylogenetic Trees by Ordered Leaf Attachment. [PDF]

Bull Math Biol
Richman DH, Zhang C, Matsen FA.
europepmc   +1 more source

Estimation of individual tree aboveground biomass of genetically diverse <i>Catalpa bungei</i> based on nonlinear mixed-effects models and UAV LiDAR data. [PDF]

Front Plant Sci
Fu X, Ma W, Chen Q, Fu L, Zhang M, Duan G, Zhang Y, Zheng Z, Wu C, Wang Q, Shun Y, Li P.   +11 more
europepmc   +1 more source

Comparing machine learning and artificial neural network models in psychological research: a ROC-based analysis. [PDF]

Front Psychol
Leitner ML, Arendasy M.
europepmc   +1 more source

Comparative evaluation of machine learning models for predicting Cimbex quadrimaculata population density across multiple problem formulations. [PDF]

PLoS One
Güral Y.
europepmc   +1 more source

Pruning tree forest and re-sampling for class imbalanced problem. [PDF]

Sci Rep
Faiz N, Iftikhar S, Jan S, Hamraz M, Aamir M, Khan DM.   +5 more
europepmc   +1 more source