Brereton, 2000, Analyst, 125, 2125, 10.1039/b003805i
Brereton, 2014, J. Chemom., 28, 213, 10.1002/cem.2609
M. L.Barker , Partial least squares for discrimination, statistical theory and implementation , LAP LAMBERT Academic Publishing , Germany , 2015
Ballabio, 2013, Anal. Methods, 5, 3790, 10.1039/c3ay40582f
Mehmood, 2016, J. Chemom., 30, 4, 10.1002/cem.2762
R. G.Brereton , Chemometrics for pattern recognition , John Wiley & Sons Ltd , Chichester, England , 2009
Kumar, 2014, Talanta, 123, 136, 10.1016/j.talanta.2014.02.003
Wu, 2017, TRAC, Trends Anal. Chem., 86, 25, 10.1016/j.trac.2016.10.013
Ahlinder, 2015, J. Chemom., 29, 267, 10.1002/cem.2699
Sattlecker, 2014, TRAC, Trends Anal. Chem., 59, 17, 10.1016/j.trac.2014.02.016
Trevisan, 2012, Analyst, 137, 2302, 10.1039/c2an16300d
Serrano-Cinca, 2013, Decis. Support Syst., 54, 1245, 10.1016/j.dss.2012.11.015
Soares, 2017, Microchem. J., 133, 258, 10.1016/j.microc.2017.03.028
Barker, 2003, J. Chemom., 17, 166, 10.1002/cem.785
L. C.Lee , C.-Y.Liong and A. A.Jemain , in Seminar Kebangsaan Institut Statistik Malaysia ke-11 (SKISM-XI) 2017 , UKM , 2017
Lee, 2016, AIP Conf. Proc., 1750, 060016, 10.1063/1.4954621
L. C.Lee , C.-Y.Liong and A. A.Jemain , in 2017 National Forensic Science Symposium (NFSS 2017) , Forensic Science Society of Malaysian , 2017
M.Grootveld , in Metabolic Profiling, Disease and Xenobiotics , Royal Society of Chemistry , England , 2012 , pp. 1–34
Gromski, 2015, Anal. Chim. Acta, 879, 10, 10.1016/j.aca.2015.02.012
Westerhuis, 2008, Metabolomics, 4, 81, 10.1007/s11306-007-0099-6
Szymanska, 2012, Metabolomics, 8, S3, 10.1007/s11306-011-0330-3
Amodio, 2017, Postharvest Biol. Technol., 125, 112, 10.1016/j.postharvbio.2016.11.013
Yang, 2017, Engineering, 9, 181, 10.4236/eng.2017.92009
Wu, 2017, PLoS One, e0175573, 10.1371/journal.pone.0175573
Vitova, 2017, BMC Nephrol., 18, 112, 10.1186/s12882-017-0519-4
Snowden, 2017, PLoS Med., 14, e1002266, 10.1371/journal.pmed.1002266
Sharma, 2017, Inflammation Res., 66, 97, 10.1007/s00011-016-0998-y
Peng, 2017, Innov. Food Sci. Emerg. Technol., 44, 212, 10.1016/j.ifset.2017.04.006
Nieuwoudt, 2017, Appl. Spectrosc., 71, 308, 10.1177/0003702816653130
Martins, 2017, Food Chem., 229, 142, 10.1016/j.foodchem.2017.02.024
Mabood, 2017, J. Adv. Dairy Res., 5, 1000167, 10.4172/2329-888X.1000167
Mabood, 2017, Food Chem., 221, 746, 10.1016/j.foodchem.2016.11.109
Li, 2017, PLoS One, 12, 0169430
Khoshmanesh, 2017, Anal. Chem., 89, 5285, 10.1021/acs.analchem.6b04827
Milanez, 2017, Microchem. J., 133, 669, 10.1016/j.microc.2017.03.004
Jorgensen, 2017, Fertil. Steril., 107, 1191, 10.1016/j.fertnstert.2017.03.013
Azcarate, 2017, Microchem. J., 130, 1, 10.1016/j.microc.2016.07.016
Garriga, 2017, Front. Plant Sci., 8, 280, 10.3389/fpls.2017.00280
DeFilippis, 2017, PLoS One, 12, e0175591, 10.1371/journal.pone.0175591
Boccio, 2017, Adv. Radiat. Oncol., 2, 118, 10.1016/j.adro.2016.12.005
Manfredi, 2017, Appl. Phys. A, 123, 35, 10.1007/s00339-016-0663-x
Georgouli, 2017, Food Chem., 217, 735, 10.1016/j.foodchem.2016.09.011
Kharbach, 2017, Chemom. Intell. Lab. Syst., 162, 182, 10.1016/j.chemolab.2017.02.003
Santos, 2017, Chemom. Intell. Lab. Syst., 161, 70, 10.1016/j.chemolab.2016.12.004
Peng, 2017, Sci. Rep., 7, 44551, 10.1038/srep44551
Bogdanovska, 2017, Saudi Pharm. J., 25, 1022, 10.1016/j.jsps.2017.03.006
Cuevas, 2017, Food Chem., 221, 1930, 10.1016/j.foodchem.2016.11.156
Reed, 2017, Neoplasia, 19, 165, 10.1016/j.neo.2016.11.003
Rios-Reina, 2017, Food Chem., 230, 108, 10.1016/j.foodchem.2017.02.118
Soares, 2017, Food Chem., 219, 1, 10.1016/j.foodchem.2016.09.127
Vermathen, 2017, Food Chem., 233, 391, 10.1016/j.foodchem.2017.04.089
Manheim, 2016, Appl. Spectrosc., 70, 1109, 10.1177/0003702816652321
Alewijn, 2016, J. Food Compos. Anal., 51, 15, 10.1016/j.jfca.2016.06.003
Valderrama, 2016, Chemom. Intell. Lab. Syst., 156, 188, 10.1016/j.chemolab.2016.06.009
Santana, 2016, Food Chem., 209, 228, 10.1016/j.foodchem.2016.04.051
Melucci, 2016, Food Chem., 204, 263, 10.1016/j.foodchem.2016.02.131
Diniz, 2016, Food Chem., 192, 374, 10.1016/j.foodchem.2015.07.022
Hou, 2016, J. Chemom., 30, 663, 10.1002/cem.2830
de Carvalho, 2016, Anal Methods, 28, 5658, 10.1039/C6AY01325B
Zotti, 2016, Food Chem., 196, 601, 10.1016/j.foodchem.2015.09.087
Rodrigues Jr., 2016, Food Chem., 196, 584, 10.1016/j.foodchem.2015.09.055
Hirri, 2016, Basic Res. J., 5, 103
Liu, 2016, J. Spectrosc., 1603609
Li, 2016, PLoS One, 11, e0168998, 10.1371/journal.pone.0168998
Borras, 2016, Food Chem., 203, 314, 10.1016/j.foodchem.2016.02.038
Shrestha, 2016, Sens. Actuators, B, 237, 1027, 10.1016/j.snb.2016.08.170
Racz, 2016, Chemom. Intell. Lab. Syst., 151, 34, 10.1016/j.chemolab.2015.11.009
Lenhardt, 2015, Food Chem., 175, 284, 10.1016/j.foodchem.2014.11.162
Ho, 2015, Forensic Sci. Int., 251, 61, 10.1016/j.forsciint.2015.03.002
Wang, 2015, Sci. Rep., 5, 18926
Mazivila, 2015, J. Braz. Chem. Soc., 26, 642
Shao, 2015, Sensor, 15, 26726, 10.3390/s151026726
Hirri, 2015, Int. J. Chem. Mater. Environ. Res., 2, 30
Moncayo, 2015, Chemom. Intell. Lab. Syst., 146, 354, 10.1016/j.chemolab.2015.06.004
Calvini, 2015, Chemom. Intell. Lab. Syst., 146, 503, 10.1016/j.chemolab.2015.07.010
Borba, 2015, Forensic Sci. Int., 249, 73, 10.1016/j.forsciint.2015.01.027
Chen, 2015, Spectrochim. Acta, Part A, 135, 185, 10.1016/j.saa.2014.07.005
Botelho, 2015, Food Chem., 181, 31, 10.1016/j.foodchem.2015.02.077
Gromski, 2014, Anal. Bioanal. Chem., 406, 7581, 10.1007/s00216-014-8216-7
Silva, 2014, Microchem. J., 116, 235, 10.1016/j.microc.2014.05.013
Paulo, 2014, Energy Fuels, 28, 4355, 10.1021/ef5003827
Tang, 2014, Spectrochim. Acta, Part A, 121, 678, 10.1016/j.saa.2013.11.104
Devos, 2014, Food Chem., 148, 124, 10.1016/j.foodchem.2013.10.020
Borras, 2014, Food Chem., 153, 15, 10.1016/j.foodchem.2013.12.032
Capuano, 2014, Food Chem., 164, 234, 10.1016/j.foodchem.2014.05.011
Gan, 2014, Food Chem., 146, 149, 10.1016/j.foodchem.2013.09.024
Drivelos, 2014, Food Chem., 165, 316, 10.1016/j.foodchem.2014.03.083
Silvestri, 2014, Chemom. Intell. Lab. Syst., 137, 181, 10.1016/j.chemolab.2014.06.012
Almeida, 2013, Microchem. J., 109, 170, 10.1016/j.microc.2012.03.006
Encyclopedia of Spectroscopy and spectrometry , ed. J. C. Lindom , G. E. Tranter and D. W. Koppennaal , Elsevier , Amsterdam , 3rd edn, 2017
Muro, 2015, Anal. Chem., 87, 306, 10.1021/ac504068a
Yang, 2003, Pattern Recognit., 36, 563, 10.1016/S0031-3203(02)00048-1
Nocairi, 2005, Comput. Stat. Data Anal., 48, 139, 10.1016/j.csda.2003.09.008
Nguyen, 2002, Bioinformatics, 18, 39, 10.1093/bioinformatics/18.1.39
Brereton, 2015, Chemom. Intell. Lab. Syst., 149, 90, 10.1016/j.chemolab.2015.06.012
Kemsley, 1996, Chemom. Intell. Lab. Syst., 33, 47, 10.1016/0169-7439(95)00090-9
Defernez, 1997, TRAC, Trends Anal. Chem., 16, 216, 10.1016/S0165-9936(97)00015-0
Marigheto, 1998, J. Am. Oil Chem. Soc., 75, 987, 10.1007/s11746-998-0276-4
Tang, 2014, PLoS One, 9, e96944, 10.1371/journal.pone.0096944
Nguyen, 2002, Bioinformatics, 18, 1216, 10.1093/bioinformatics/18.9.1216
Ciosek, 2005, Talanta, 67, 590, 10.1016/j.talanta.2005.03.006
Kjedahl, 2010, J. Chemom., 24, 558, 10.1002/cem.1346
Filzmoser, 2012, J. Chemom., 26, 42, 10.1002/cem.1418
Brereton, 2006, TRAC, Trends Anal. Chem., 25, 1103, 10.1016/j.trac.2006.10.005
Perez, 2009, Chemom. Intell. Lab. Syst., 95, 122, 10.1016/j.chemolab.2008.09.005
Botella, 2009, Talanta, 80, 321, 10.1016/j.talanta.2009.06.072
Galtier, 2011, Vib. Spectrosc., 55, 132, 10.1016/j.vibspec.2010.09.012
Serrano-Lourido, 2012, Food Chem., 135, 1425, 10.1016/j.foodchem.2012.06.010
Engel, 2013, TRAC, Trends Anal. Chem., 50, 96, 10.1016/j.trac.2013.04.015
Lasch, 2012, Chemom. Intell. Lab. Syst., 117, 100, 10.1016/j.chemolab.2012.03.011
Lee, 2017, AIP Conf. Proc., 1830, 080008, 10.1063/1.4980992
Rinnan, 2009, TRAC, Trends Anal. Chem., 28, 1201, 10.1016/j.trac.2009.07.007
Bocklitz, 2011, Anal. Chim. Acta, 704, 47, 10.1016/j.aca.2011.06.043
A. R.Webb and K. D.Copsey , Statistical Pattern Recognition , Wiley , Chichester , 3rd edn, 2011
Guyon, 2003, J. Mach. Learn. Res., 3, 1157
Xie, 2015, Sci. Rep., 5, 10930, 10.1038/srep10930
Yin, 2016, Anal. Methods, 13, 2794, 10.1039/C6AY00259E
Cheng, 2016, Food Chem., 197, 855, 10.1016/j.foodchem.2015.11.019
Aliakbarzadeh, 2016, Chemom. Intell. Lab. Syst., 158, 165, 10.1016/j.chemolab.2016.09.002
Mehmood, 2012, Chemom. Intell. Lab. Syst., 118, 62, 10.1016/j.chemolab.2012.07.010
Devos, 2011, Chemom. Intell. Lab. Syst., 107, 50, 10.1016/j.chemolab.2011.01.008
Andersen, 2010, J. Chemom., 24, 728, 10.1002/cem.1360
Issakson, 2008, Pattern Recognit. Lett., 29, 1960, 10.1016/j.patrec.2008.06.018
Martens, 1998, Chemom. Intell. Lab. Syst., 44, 99, 10.1016/S0169-7439(98)00167-1
Esbensen, 2010, J. Chemom., 24, 168, 10.1002/cem.1310
Arlot, 2010, Stat. Surveys, 4, 40, 10.1214/09-SS054
Breiman, 1992, Int. Stat. Rev., 60, 291, 10.2307/1403680
T.Hastie , R.Tibshirani and J. H.Friedman , in The Elements of Statistical Learning, Data Mining, Inference and Prediction , Springer , New York , 2009 , ch. 7.10, pp. 214–217
Galvao, 2005, Talanta, 67, 736, 10.1016/j.talanta.2005.03.025
Daszykowski, 2002, Anal. Chim. Acta, 468, 91, 10.1016/S0003-2670(02)00651-7
Goot, 1999, Anal. Chim. Acta, 392, 67, 10.1016/S0003-2670(99)00193-2
T.Borovicka , M.Jirina Jr. , P.Kordik and M.Jirina , in Advances in Data Mining Knowledge discovery and applications , InTech , Croatia , 2012
Wehrens, 2000, Chemom. Intell. Lab. Syst., 54, 35, 10.1016/S0169-7439(00)00102-7
P.Golland , F.Liang , S.Mukherjee and D.Panchenko , in Learning Theory , Springer , Berlin/Heidelberg , 2005 , pp. 501–515
http://wiki.eigenvector.com/index.php?title=Using_Cross-Validation
Kennard, 1969, Technometrics, 11, 137, 10.1080/00401706.1969.10490666
Quintas, 2012, Metabolomics, 8, 86, 10.1007/s11306-011-0292-5
Rojas, 2017, Front. Chem., 5, 53, 10.3389/fchem.2017.00053
Hawkins, 2010, J. Chemom., 24, 188, 10.1002/cem.1311
Molinaro, 2005, Bioinformatics, 21, 3301, 10.1093/bioinformatics/bti499
Filzmoser, 2009, J. Chemom., 23, 160, 10.1002/cem.1225
T.Hastie , R.Tibshirani and J.Friedman , The wrong and right way to do cross-validation , in Elements of Statistical Learning, Data Mining, Inference, Prediction , Springer , NY , 2009 , pp. 245–247
Chevallier, 2006, J. Chemom., 20, 221, 10.1002/cem.994
Bylesjo, 2006, J. Chemom., 20, 341, 10.1002/cem.1006
G.James , D.Witten , T.Hastie and R.Tibshiranim , Assessing Model Accuracy , in An introduction to statistical learning , Springer , New York , 2013 , pp. 29–36
Brown, 2006, Chemom. Intell. Lab. Syst., 80, 24, 10.1016/j.chemolab.2005.05.004
Reid, 2005, Food Res. Int., 38, 1109, 10.1016/j.foodres.2005.03.005
Dixon, 2009, Chemom. Intell. Lab. Syst., 99, 111, 10.1016/j.chemolab.2009.07.016
Smit, 2007, Anal. Chim. Acta, 592, 210, 10.1016/j.aca.2007.04.043
Efron, 1983, J. Am. Stat. Assoc., 78, 316, 10.1080/01621459.1983.10477973
P.Refaeilzadeh , L.Tang and H.Liu , in Encyclopedia of Database systems , Springer , New York , 2009 , pp. 532–538
Xu, 2004, J. Chemom., 19, 112, 10.1002/cem.858
Xu, 2001, Chemom. Intell. Lab. Syst., 56, 1, 10.1016/S0169-7439(00)00122-2
Krakowska, 2015, Analyst, 141, 1060, 10.1039/C5AN01656H
A. J.Izenman , in Modern Multivariate Statistical Techniques , Springer , England , 2013 , pp. 237–280
Brereton, 2011, J. Chemom., 25, 225, 10.1002/cem.1397
Lorena, 2011, Expert Syst. Appl., 38, 5268, 10.1016/j.eswa.2010.10.031
Noord, 1994, Chemom. Intell. Lab. Syst., 23, 65, 10.1016/0169-7439(93)E0065-C
Hawkins, 2004, J. Chem. Inf. Comput. Sci., 44, 1, 10.1021/ci0342472
