Results 81 to 90 of about 338,729 (282)
A random forest system combination approach for error detection in digital dictionaries [PDF]
, 2014 When digitizing a print bilingual dictionary, whether via optical character recognition or manual entry, it is inevitable that errors are introduced into the electronic version that is created. We investigate automating the process of detecting errors in
Bloodgood, Michael +4 more
core
Bioinformatics, 2008 Abstract Although the random forest classification procedure works well in datasets with many features, when the number of features is huge and the percentage of truly informative features is small, such as with DNA microarray data, its performance tends to decline significantly.
Dhammika Amaratunga +2 more
openaire +2 more sources
Von Economo Neuron Loss in Frontotemporal Dementia: A Meta‐Analysis of Neuropathological Studies
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Von Economo neurons (VENs) have been reported to be vulnerable to neurodegeneration in frontotemporal dementia (FTD), particularly the behavioral variant (bvFTD), but these findings have not been systematically assessed across independent brain banks.
Daniel Talmasov +2 more
wiley +1 more source
Elevated Connectivity During Language Processing Is Associated With Cognitive Performance in SeLECTS
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Self‐Limited Epilepsy with Centrotemporal Spikes (SeLECTS) is associated with language impairments despite seizures originating in the motor cortex, suggesting aberrant cross‐network interactions. Here we tested whether functional connectivity in SeLECTS during language tasks predicts language performance.
Wendy Qi +8 more
wiley +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
IEICE Transactions on Information and Systems, 2015 Machine learning is used in various fields and demand for implementations is increasing. Within machine learning, a Random Forest is a multi-class classifier with high-performance classification, achieved using bagging and feature selection, and is capable of high-speed training and classification. However, as a type of ensemble learning, Random Forest
Yohei Mishina +4 more
openaire +2 more sources
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background and Purpose White matter hyperintensities (WMH) are a core neuroimaging marker of cerebral small vessel disease (CSVD). Sleep apnoea (SA) is a recognized vascular risk factor, but its associations with regional WMH burden, short‐interval WMH change and cognitive performance in population‐based cohorts remain incompletely defined. We
Peng Cheng +4 more
wiley +1 more source
Random KNN feature selection - a fast and stable alternative to Random Forests
BMC Bioinformatics, 2011 Background Successfully modeling high-dimensional data involving thousands of variables is challenging. This is especially true for gene expression profiling experiments, given the large number of genes involved and the small number of samples available.
Li Shengqiao +2 more
doaj +1 more source
Analysis of a Random Forests Model [PDF]
, 2012 Random forests are a scheme proposed by Leo Breiman in the 2000's for building a predictor ensemble with a set of decision trees that grow in randomly selected subspaces of data.
Bin Yu, Gérard Biau Lsta
core +1 more source
On the shape of random P\'olya structures
, 2018 Panagiotou and Stufler recently proved an important fact on their way to establish the scaling limits of random P\'olya trees: a uniform random P\'olya tree of size $n$ consists of a conditioned critical Galton-Watson tree $C_n$ and many small forests ...
Gittenberger, Bernhard +2 more
core +2 more sources