Results 41 to 50 of about 360,197 (329)
Discriminating between glaucoma and normal eyes using optical coherence tomography and the 'Random Forests' classifier. [PDF]
PLoS ONE, 2014 To diagnose glaucoma based on spectral domain optical coherence tomography (SD-OCT) measurements using the 'Random Forests' method.SD-OCT was conducted in 126 eyes of 126 open angle glaucoma (OAG) patients and 84 eyes of 84 normal subjects.
Tatsuya Yoshida +6 more
doaj +1 more source
A simple and effective approach to quantitatively characterize structural complexity
Scientific Reports, 2021 This study brings insight into interpreting forest structural diversity and explore the classification of individuals according to the distribution of the neighbours in natural forests. Natural forest communities with different latitudes and distribution
Gongqiao Zhang +3 more
doaj +1 more source
Random Forests and Networks Analysis
, 2017 D. Wilson~\cite{[Wi]} in the 1990's described a simple and efficient algorithm based on loop-erased random walks to sample uniform spanning trees and more generally weighted trees or forests spanning a given graph. This algorithm provides a powerful tool
Avena, L. +3 more
core +3 more sources
Enhancing random forests performance in microarray data classification [PDF]
, 2013 Random forests are receiving increasing attention for classification of microarray datasets. We evaluate the effects of a feature selection process on the performance of a random forest classifier as well as on the choice of two critical parameters, i.e.
DESSI, NICOLETTA +2 more
core +1 more source
, 2019 Space partitioning methods such as random forests and the Mondrian process are powerful machine learning methods for multi-dimensional and relational data, and are based on recursively cutting a domain. The flexibility of these methods is often limited by the requirement that the cuts be axis aligned.
Ge, S +4 more
openaire +3 more sources
Prediction of unconventional protein secretion by exosomes
BMC Bioinformatics, 2021 Motivation In eukaryotes, proteins targeted for secretion contain a signal peptide, which allows them to proceed through the conventional ER/Golgi-dependent pathway.
Alvaro Ras-Carmona +2 more
doaj +1 more source
, 2012 We consider unimodular random rooted trees (URTs) and invariant forests in Cayley graphs. We show that URTs of bounded degree are the same as the law of the component of the root in an invariant percolation on a regular tree.
Aldous +5 more
core +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Objectives To identify predictors of chronic ITP (cITP) and to develop a model based on several machine learning (ML) methods to estimate the individual risk of chronicity at the timepoint of diagnosis. Methods We analyzed a longitudinal cohort of 944 children enrolled in the Intercontinental Cooperative immune thrombocytopenia (ITP) Study ...
Severin Kasser +6 more
wiley +1 more source
Block Forests: random forests for blocks of clinical and omics covariate data
BMC Bioinformatics, 2019 Background In the last years more and more multi-omics data are becoming available, that is, data featuring measurements of several types of omics data for each patient. Using multi-omics data as covariate data in outcome prediction is both promising and
Roman Hornung, Marvin N. Wright
doaj +1 more source
Journal of Combinatorial Theory, Series A, 1999 Suppose that rooted forests (in which the edges in each tree are directed away from the root of the tree) are formed by starting with a set of \(n\) labelled vertices and succesively adding an edge \(uv\) from a randomly chosen vertex \(u\) to the root \(v\) of a randomly chosen tree not containing \(u\). The author derives several enumeration formulae
openaire +1 more source