The spectrum-based learner: A new local approach for modeling soil vis-NIR spectra of complex datasets

Geoderma

Volumn 195-196, Issue , 2013, Pages 268-279

  Ramirez Lopez, Leonardo ^a,b   Behrens, Thorsten ^a   Schmidt, Karsten ^a   Stevens, Antoine ^b   Demattê, Jose Alexandre M ^c   Scholten, Thomas ^a  

^a UNIVERSITY OF TÜBINGEN   (Germany)

^b UNIVERSITÉ CATHOLIQUE DE LOUVAIN   (Belgium)

^c UNIVERSITY OF SÃO PAULO   (Brazil)

Author keywords

Local modeling; Machine learning; Memory based learning; Nearest neighbor; Soil similarity; Soil spectral library

Indexed keywords

CALIBRATED MODEL; CLAY CONTENT; COMPLEX DATASETS; COMPLEX SOILS; DATA SETS; DISTANCE MATRICES; GAUSSIAN PROCESS REGRESSION; LOCAL APPROACHES; LOCAL MODELING; MEMORY-BASED LEARNING; NEAREST NEIGHBORS; PARTIAL LEAST-SQUARES REGRESSION; PLS REGRESSION; PREDICTION PERFORMANCE; PREDICTIVE PERFORMANCE; PREDICTOR VARIABLES; PRINCIPAL COMPONENTS; SPECTRAL FEATURE; SPECTRAL LIBRARIES; SPECTRAL MODELS; SUPPORT VECTOR REGRESSION MACHINES; VIS-NIR SPECTRA; VISIBLE AND NEAR INFRARED;

ALGORITHMS; INFRARED DEVICES; LEARNING SYSTEMS; PRINCIPAL COMPONENT ANALYSIS; REGRESSION ANALYSIS; SOILS;

GEOLOGIC MODELS;

ACCURACY ASSESSMENT; ALGORITHM; CALIBRATION; DATA SET; GAUSSIAN METHOD; NUMERICAL MODEL; PREDICTION; REGRESSION ANALYSIS; SOIL ANALYSIS; SOIL PROPERTY; SPECTRAL ANALYSIS; SPECTROSCOPY; SPECTRUM;

BRAZIL; SAO PAULO [BRAZIL];

EID: 84872743699     PISSN: 00167061     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.geoderma.2012.12.014     Document Type: Article

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