About: Less is more: optimizing classification performance through feature selection in a very-high-resolution remote sensing object-based urban application

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article by Stefanos Georganos et al published 30 November 2017 in GIScience & remote sensing

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rdf:type	Item
description	wetenschappelijk artikel (nl) article scientifique publié en 2017 (fr) наукова стаття, опублікована в листопаді 2017 (uk) im November 2017 veröffentlichter wissenschaftlicher Artikel (de) article by Stefanos Georganos et al published 30 November 2017 in GIScience & remote sensing (en)
publication date	wds:Q59206887-4AAD32D6-2D8C-4B3E-8BBC-EA909663369D
publication date	2017-11-30 00:00:00Z (xsd:dateTime)
cites work	wds:Q59206887-2047C56D-6309-4266-9FB1-6B711DF31EC8 wds:Q59206887-730D2C50-3D5E-42AB-90BF-3E1383B215D8 wds:Q59206887-7D21731B-E91D-4B7D-975C-64AF7933DCC9 wds:Q59206887-8EE4A144-3D1A-4E93-A5F5-84323362C687 wds:Q59206887-934CDD3A-1A58-4444-A369-6F4FE49A39A4 wds:Q59206887-9433F859-B3FE-4B88-AF76-61FBA6C3BCA9 wds:Q59206887-BDCF0F1B-564D-433E-87B5-BDC4D898895A wds:Q59206887-DAFDFFCE-E265-4E83-9A21-C8E52B2223E2 wds:Q59206887-DFC97360-8BC0-4145-A5AA-38714FE7C59F wds:Q59206887-E026B312-C245-4E76-AD1D-983BF896E482 wds:Q59206887-F33DE5A9-8B80-4D80-BFE2-7A45C13C5193 wds:Q59206887-F3FB47E2-EA5F-4036-8470-A98D5A2D55F8
cites work	Identifying Important Risk Factors for Survival in Kidney Graft Failure Patients Using Random Survival Forests Geographic Object-Based Image Analysis - Towards a new paradigm GRASS GIS: A multi-purpose open source GIS Random Forest classification of Mediterranean land cover using multi-seasonal imagery and multi-seasonal texture Bias in random forest variable importance measures: illustrations, sources and a solution The behaviour of random forest permutation-based variable importance measures under predictor correlation On the mean accuracy of statistical pattern recognizers Geostatistical modelling of the malaria risk in Mozambique: effect of the spatial resolution when using remotely-sensed imagery An Open-Source Semi-Automated Processing Chain for Urban Object-Based Classification Bioactive Molecule Prediction Using Extreme Gradient Boosting Examining the NDVI-rainfall relationship in the semi-arid Sahel using geographically weighted regression Unbiased feature selection in learning random forests for high-dimensional data
author name string	wds:Q59206887-24F205A2-0636-41B1-A129-97D4619F0F80 wds:Q59206887-533E7EC3-A62E-452D-ABF2-DE164BC5304C wds:Q59206887-90574867-8D66-4498-BBAA-71280211B3D4 wds:Q59206887-B5DBAFF5-A2DF-4A7A-8AFC-F5796A4CC26B wds:Q59206887-C7ED8A82-80A8-475E-812E-8B9B7AABD3A0 wds:Q59206887-C9241B6D-A51F-46DA-BA75-BA0A288EDFEA wds:Q59206887-F505BA61-0F1D-48F8-8B5D-95CE0235D638
author name string	Moritz Lennert Sabine Vanhuysse Stefanos Georganos Tais Grippa Stamatis Kalogirou Eleonore Wolff Michal Shimoni
rdfs:label	Less is more: optimizing classification performance through feature selection in a very-high-resolution remote sensing object-based urban application (en) Less is more: optimizing classification performance through feature selection in a very-high-resolution remote sensing object-based urban application (nl)
skos:prefLabel	Less is more: optimizing classification performance through feature selection in a very-high-resolution remote sensing object-based urban application (en) Less is more: optimizing classification performance through feature selection in a very-high-resolution remote sensing object-based urban application (nl)
name	Less is more: optimizing classification performance through feature selection in a very-high-resolution remote sensing object-based urban application (en) Less is more: optimizing classification performance through feature selection in a very-high-resolution remote sensing object-based urban application (nl)
title	wds:Q59206887-47964104-4A23-44F5-9108-B2B497306663
title	Less is more: optimizing classification performance through feature selection in a very-high-resolution remote sensing object-based urban application (en)
page(s)	wds:Q59206887-E21F3621-AC94-470C-B131-3149D5F1820D
page(s)	221-242
instance of	wds:Q59206887-138C8EF1-7193-4D3D-8D23-E955582BF68F
instance of	scholarly article
main subject	wds:Q59206887-389694C3-2AF2-45C0-B71F-25E539FB60FF wds:Q59206887-E16247D8-48A3-42DA-A248-D6CB717C8226
main subject	feature selection remote sensing
published in	wds:Q59206887-7974E436-8E0D-407A-8AD9-F0CBCCC066EF
published in	GIScience & remote sensing
issue	wds:Q59206887-B9385215-A072-4511-985A-FD028D2E7ABF
volume	wds:Q59206887-3737289E-C906-4CCA-B6E5-20E5561FF9CB
issue	2
volume	55
DOI	wds:Q59206887-49963921-4CF1-4B77-868B-0AA05E80F452
DOI	http://dx.doi.org/10.1080/15481603.2017.1408892
DOI	10.1080/15481603.2017.1408892
is about of	https://www.wikidata.org/wiki/Special:EntityData/Q59206887

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