Results 11 to 20 of about 86,959 (305)
Tracking Cloud Forests With Cloud Technology and Random Forests
Frontiers in Environmental Science, 2021 Hotspots of endemic biodiversity, tropical cloud forests teem with ecosystem services such as drinking water, food, building materials, and carbon sequestration. Unfortunately, already threatened by climate change, the cloud forests in our study area are
Pasky Pascual, Cam Pascual
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Multi-Class Assessment Based on Random Forests
Education Sciences, 2021 Today, many students are moving towards higher education courses that do not suit them and end up failing. The purpose of this study is to help provide counselors with better knowledge so that they can offer future students courses corresponding to their
Mehdi Berriri +3 more
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EDRN/random-decision-forests: 1.0.0
, 2021 This is the initial "general availability" (GA) or "first customer ship" (FCS) of Random Decision ...
Sean Kelly
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Statistical Analysis and Data Mining: The ASA Data Science Journal, 2021 AbstractsidClustering is a new random forests unsupervised machine learning algorithm. The first step in sidClustering involves what is called sidification of the features: staggering the features to have mutually exclusive ranges (called the staggered interaction data [SID] main features) and then forming all pairwise interactions (called the SID ...
Alejandro Mantero, Hemant Ishwaran
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JalalAl-Tamimi/Intro-Random-Forests: first release
, 2022 This repo contains material for a workshop on Random Forests in phonetics/phonology ...
Jalal Al-Tamimi
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Using random forests to model 90-day hometime in people with stroke
BMC Medical Research Methodology, 2021 Background Ninety-day hometime, the number of days a patient is living in the community in the first 90 after stroke, exhibits a non-normal bucket-shaped distribution, with lower and upper constraints making its analysis difficult.
Jessalyn K. Holodinsky +3 more
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Machine Learning, 2020 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Sunwoo Han, Hyunjoong Kim, Yung-Seop Lee
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Machine Learning, 2001 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Predicting equity market price impact with performance weighted ensembles of random forests [PDF]
, 2014 For many players in financial markets, the price impact of their trading activity represents a large proportion of their transaction costs. This paper proposes a novel machine learning method for predicting the price impact of order book events ...
Enrico Gerding +5 more
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Evaluation of random forests and Prophet for daily streamflow forecasting [PDF]
Advances in Geosciences, 2018 We assess the performance of random forests and Prophet in forecasting daily streamflow up to seven days ahead in a river in the US. Both the assessed forecasting methods use past streamflow observations, while random forests additionally use past ...
G. A. Papacharalampous +3 more
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