The Naïve Overfitting Index Selection (NOIS): A new method to optimize model complexity for hyperspectral data

Alby Duarte Rocha, Thomas A. Groen, Andrew K. Skidmore, Roshanak Darvishzadeh, L. Willemen

Research output: Contribution to journal › Article › Academic › peer-review

3 Citations (Scopus)
2 Downloads (Pure)
Original languageEnglish
Pages (from-to)61-74
JournalISPRS journal of photogrammetry and remote sensing
Volume133
DOIs
Publication statusPublished - 1 Nov 2017

Keywords

  • ITC-ISI-JOURNAL-ARTICLE

Cite this

Duarte Rocha, Alby ; Groen, Thomas A. ; Skidmore, Andrew K. ; Darvishzadeh, Roshanak ; Willemen, L. / The Naïve Overfitting Index Selection (NOIS) : A new method to optimize model complexity for hyperspectral data. In: ISPRS journal of photogrammetry and remote sensing. 2017 ; Vol. 133. pp. 61-74.
@article{bf15903bc4444be2a8cd816881449838,
title = "The Na{\"i}ve Overfitting Index Selection (NOIS): A new method to optimize model complexity for hyperspectral data",
keywords = "ITC-ISI-JOURNAL-ARTICLE",
author = "{Duarte Rocha}, Alby and Groen, {Thomas A.} and Skidmore, {Andrew K.} and Roshanak Darvishzadeh and L. Willemen",
year = "2017",
month = "11",
day = "1",
doi = "10.1016/j.isprsjprs.2017.09.012",
language = "English",
volume = "133",
pages = "61--74",
journal = "ISPRS journal of photogrammetry and remote sensing",
issn = "0924-2716",
publisher = "Elsevier",

}

Duarte Rocha, A, Groen, TA, Skidmore, AK, Darvishzadeh, R & Willemen, L 2017, 'The Naïve Overfitting Index Selection (NOIS): A new method to optimize model complexity for hyperspectral data', ISPRS journal of photogrammetry and remote sensing, vol. 133, pp. 61-74. https://doi.org/10.1016/j.isprsjprs.2017.09.012

The Naïve Overfitting Index Selection (NOIS) : A new method to optimize model complexity for hyperspectral data. / Duarte Rocha, Alby ; Groen, Thomas A.; Skidmore, Andrew K.; Darvishzadeh, Roshanak; Willemen, L.

In: ISPRS journal of photogrammetry and remote sensing, Vol. 133, 01.11.2017, p. 61-74.

Research output: Contribution to journal › Article › Academic › peer-review

TY - JOUR

T1 - The Naïve Overfitting Index Selection (NOIS)

T2 - A new method to optimize model complexity for hyperspectral data

AU - Duarte Rocha, Alby

AU - Groen, Thomas A.

AU - Skidmore, Andrew K.

AU - Darvishzadeh, Roshanak

AU - Willemen, L.

PY - 2017/11/1

Y1 - 2017/11/1

KW - ITC-ISI-JOURNAL-ARTICLE

UR - https://ezproxy2.utwente.nl/login?url=https://webapps.itc.utwente.nl/library/2017/isi/skidmore_nai.pdf

U2 - 10.1016/j.isprsjprs.2017.09.012

DO - 10.1016/j.isprsjprs.2017.09.012

M3 - Article

VL - 133

SP - 61

EP - 74

JO - ISPRS journal of photogrammetry and remote sensing

JF - ISPRS journal of photogrammetry and remote sensing

SN - 0924-2716

ER -

Duarte Rocha A, Groen TA, Skidmore AK, Darvishzadeh R, Willemen L. The Naïve Overfitting Index Selection (NOIS): A new method to optimize model complexity for hyperspectral data. ISPRS journal of photogrammetry and remote sensing. 2017 Nov 1;133:61-74. https://doi.org/10.1016/j.isprsjprs.2017.09.012

Access to Document

Related content

Datasets

Model overfitting using hyperspectral remote sensing

Dataset