Study on an Algorithm for Near Infrared Spectrum Multiclass Identification and Measurement Based on Feature Hierarchical Selection and Sample Fusion Degree

ZHU Cheng; GONG Hui-li; DING Xiang-qian; HOU Rui-chun

doi:10.3964/j.issn.1000-0593(2017)04-1095-05

Journals >Spectroscopy and Spectral Analysis >Volume 37 >Issue 4 >Page 1095 > Article

Spectroscopy and Spectral Analysis
Vol. 37, Issue 4, 1095 (2017)

Study on an Algorithm for Near Infrared Spectrum Multiclass Identification and Measurement Based on Feature Hierarchical Selection and Sample Fusion Degree

ZHU Cheng, GONG Hui-li, DING Xiang-qian, and HOU Rui-chun

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[in Chinese]

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DOI: 10.3964/j.issn.1000-0593(2017)04-1095-05 Cite this Article

ZHU Cheng, GONG Hui-li, DING Xiang-qian, HOU Rui-chun. Study on an Algorithm for Near Infrared Spectrum Multiclass Identification and Measurement Based on Feature Hierarchical Selection and Sample Fusion Degree[J]. Spectroscopy and Spectral Analysis, 2017, 37(4): 1095 Copy Citation Text

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References

[2] Philip Williams, Karl Norris. Near Infrared Technology in the Agriculture and Food Industries. 2nd ed. Inc. St., American Association of Cereal Chemists, Minnesota USA: AACC, 2001.

[6] Ni Lijin, Zhang Liguo, Xie Juan, et al. Analytical Chemica Acta, 2009, 633: 43.

[10] Leo Breiman. Random Forests. Machine Learning, 2001, 45(1): 5.

[13] Simon Bernard, Laurent Heutte, Sebastien Adam. Lecture Notes in Computer Science, 2009, 5519: 171.

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