machine learning tool c5.0tm (Rulequest Research Pty Ltd)
90
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Rulequest Research Pty Ltd
machine learning tool c5.0tm
Machine Learning Tool C5.0tm, supplied by Rulequest Research Pty Ltd, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/machine+learning+assisted+annotation+tool/c5+0+algorithm/us07796937-209-7-19
Average 90 stars, based on 1 article reviews
Machine Learning Tool C5.0tm, supplied by Rulequest Research Pty Ltd, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/machine+learning+assisted+annotation+tool/c5+0+algorithm/us07796937-209-7-19
Average 90 stars, based on 1 article reviews
machine learning tool c5.0tm - by Bioz Stars,
2026-11
90/100 stars
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other:Article Title: Geo-parcel-based geographical thematic mapping using C5.0 decision tree: a case study of evaluating sugarcane planting suitability Article Snippet: Geographical thematic mapping based on spatial information can effectively support scientific decision-making in Geosciences.. To obtain finer spatial decision information, this paper proposes a geo-parcel-based thematic mapping methodology for evaluating cash crop planting suitability using C5.0 decision tree (DT).. In this study, geo-parcels are utilized as basic mapping units. Article Title: The Potential of Big Housing Data: An Application to the Italian Real-Estate Market Article Snippet: Electronic copy available at: https://ssrn.com/abstract=3176962 Temi di discussione (Working Papers) The potential of big housing data: an application to the Italian real-estate market by Michele Loberto, Andrea Luciani and Marco Pangallo N um be r 1171April 20 18 Electronic copy available at: https://ssrn.com/abstract=3176962 Electronic copy available at: https://ssrn.com/abstract=3176962 Temi di discussione (Working Papers) The potential of big housing data: an application to the Italian real-estate market by Michele Loberto, Andrea Luciani and Marco Pangallo Number 1171 - April 2018 The papers published in the Temi di discussione series describe preliminary results and are made available to the public to encourage discussion and elicit comments.. The views expressed in the articles are those of the authors and do not involve the responsibility of the Bank.. Editorial Board: Antonio Bassanetti, Marco Casiraghi, Emanuele Ciani, Vincenzo Cuciniello, Nicola Curci, Davide Delle Monache, Giuseppe Ilardi, Andrea Linarello, Juho Taneli Makinen, Valentina Michelangeli, Valerio Nispi Landi, Marianna Riggi, Lucia Paola Maria Rizzica, Massimiliano Stacchini. Article Title: Machine learning-, rule- and pharmacophore-based classification on the inhibition of P-glycoprotein and NorA Article Snippet: The efflux pumps P-glycoprotein (P-gp) in humans and NorA in Staphylococcus aureus are of great interest for medicinal chemists because of their important roles in multidrug resistance (MDR).. The high polyspecificity as well as the unavailability of high-resolution X-ray crystal structures of these transmembrane proteins lead us to combining ligand-based approaches, which in the case of this study were machine learning, perceptual mapping and pharmacophore modelling.. For P-gp inhibitory activity, individual models were developed using different machine learning algorithms and subsequently combined into an ensemble model which showed a good discrimination between inhibitors and noninhibitors (acctraindiverse = 84%; accinternal-test = 92% and accexternal-test = 100%). Article Title: Early identification of potato storage disease using an array of metal-oxide based gas sensors Article Snippet: Soft rot is a widespread potato tuber disease that causes substantial losses each year to the UK potato industry.. In this work, it was explored the possibility for the early detection and monitoring of this disease by means of gas sensing in a laboratory setting.. Potato tubers were inoculated with one type of bacterium which can cause soft rot, Pectobacterium carotovorum, and stored in controlled conditions conducive to rapid disease progression. Article Title: Detection by active spatially and spectrally structured sensing and learning (DAS4L) Article Snippet: Article Title: Automated Analysis of Diffusion‐Weighted Magnetic Resonance Imaging for the Differential Diagnosis of Multiple System Atrophy from Parkinson's Disease Article Snippet: A C5.0 decision tree to classify patients with PD and MSA informed by MD, FA, and volume measurements from Article Title: Learning to see the wood for the trees: machine learning, decision trees, and the classification of isolated theropod teeth Article Snippet: Taxonomic identification of fossils based on morphometric data traditionally relies on the use of standard linear models to classify such data.. Machine learning and decision trees offer powerful alternative approaches to this problem but are not widely used in palaeontology.. Here, we apply these techniques to published morphometric data of isolated theropod teeth in order to explore their utility in tackling taxonomic problems. |