{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T01:57:35Z","timestamp":1775181455207,"version":"3.50.1"},"publisher-location":"London","reference-count":19,"publisher":"Springer London","isbn-type":[{"value":"9781846282232","type":"print"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"DOI":"10.1007\/1-84628-224-1_16","type":"book-chapter","created":{"date-parts":[[2007,10,26]],"date-time":"2007-10-26T07:50:33Z","timestamp":1193385033000},"page":"209-222","source":"Crossref","is-referenced-by-count":56,"title":["The Effect of Principal Component Analysis on Machine Learning Accuracy with High Dimensional Spectral Data"],"prefix":"10.1007","author":[{"given":"Tom","family":"Howley","sequence":"first","affiliation":[]},{"given":"Michael G.","family":"Madden","sequence":"additional","affiliation":[]},{"given":"Marie-Louise","family":"O\u2019Connell","sequence":"additional","affiliation":[]},{"given":"Alan G.","family":"Ryder","sequence":"additional","affiliation":[]}],"member":"297","reference":[{"key":"16_CR1","doi-asserted-by":"publisher","first-page":"358","DOI":"10.1016\/S0014-5793(03)01275-4","volume":"555","author":"S. Peng","year":"2003","unstructured":"Peng, S., Xu, Q., Ling, X., Peng, X., Du, W., Chen, L.: Molecular Classification of Cancer Types from Microarray Data using the combination of Genetic Algorithms and Support Vector Machines. FEBS Letters 555 (2003) 358\u2013362","journal-title":"FEBS Letters"},{"key":"16_CR2","unstructured":"Wang, J., Kwok, J., Shen, H., Quan, L.: Data-dependent kernels for small-scale, high-dimensional data classification. In: Proc. of the International Joint Conference on Neural Networks (to appear). (2005)"},{"key":"16_CR3","doi-asserted-by":"crossref","unstructured":"Joachims, T.: Text categorisation with support vector machines. In: Proceedings of European Conference on Machine Learning (ECML). (1998)","DOI":"10.1007\/BFb0026683"},{"key":"16_CR4","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1520\/JFS15244J","volume":"47","author":"A. Ryder","year":"2002","unstructured":"Ryder, A.: Classification of narcotics in solid mixtures using Principal Component Analysis and Raman spectroscopy and chemometric methods. J. Forensic Sci 47 (2002) 275\u2013284","journal-title":"J. Forensic Sci"},{"key":"16_CR5","volume-title":"The Raman effect: an introduction","author":"B. Bulkin","year":"1991","unstructured":"Bulkin, B.: The Raman effect: an introduction. New York: John Wiley and Sons, Inc (1991)"},{"key":"16_CR6","doi-asserted-by":"crossref","unstructured":"Conroy, J., Ryder, A., Leger, M., Hennessy, K., Madden, M.: Qualitative and quantitative analysis of chlorinated solvents using Raman spectroscopy and machine learning. In: Proc. SPIE-Int. Soc. Opt. Eng. Volume 5826 (in press). (2005)","DOI":"10.1117\/12.605056"},{"key":"16_CR7","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1520\/JFS13756J","volume":"40","author":"C. Cheng","year":"1995","unstructured":"Cheng, C., Kirkbride, T., Batchelder, D., Lacey, R., Sheldon, T.: In situ detection and identification of trace explosives by Raman microscopy. J. Forensic Sci 40 (1995)31\u201337","journal-title":"J. Forensic Sci"},{"key":"16_CR8","doi-asserted-by":"crossref","unstructured":"O\u2019Connell, M., Howley, T., Ryder, A., Leger, M., Madden, M.: Classification of a target analyte in solid mixtures using principal component analysis, support vector machines and Raman spectroscopy. In: Proc. SPIE-Int. Soc. Opt. Eng. Volume 5826 (in press). (2005)","DOI":"10.1117\/12.605156"},{"key":"16_CR9","doi-asserted-by":"crossref","unstructured":"Hastie, T., Tibshirani, R., Friedman, J.: The Elements of Statistical Learning. Springer (2001)","DOI":"10.1007\/978-0-387-21606-5"},{"key":"16_CR10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/0003-2670(86)80028-9","volume":"185","author":"P. Geladi","year":"1986","unstructured":"Geladi, P., Kowalski, B.: Partial Least Squares: A Tutorial. Analytica Chemica Acta 185 (1986) 1\u201317","journal-title":"Analytica Chemica Acta"},{"key":"16_CR11","doi-asserted-by":"crossref","unstructured":"Scholkopf, B., Smola, A.: Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. MIT Press (2002)","DOI":"10.7551\/mitpress\/4175.001.0001"},{"key":"16_CR12","unstructured":"Witten, I., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations. Morgan Kaufmann Publishers (2000)"},{"key":"16_CR13","doi-asserted-by":"crossref","unstructured":"Quinlan, R.: Learning Logical Definitions from Relations. Machine Learning 5 (1990)","DOI":"10.1007\/BF00117105"},{"key":"16_CR14","unstructured":"Cohen, W.: Fast Eeffective Rule Induction. In: Proc. of the 12th Int. Conference on Machine Learning. (2002) 115\u2013123"},{"key":"16_CR15","doi-asserted-by":"publisher","first-page":"1627","DOI":"10.1021\/ac60214a047","volume":"36","author":"A. Savitzky","year":"1964","unstructured":"Savitzky, A., Golay, M.: Smoothing and differentiation of data by simplified least squares procedures. Anal. Chem. 36 (1964) 1627\u20131639","journal-title":"Anal. Chem."},{"key":"16_CR16","unstructured":"Nadeau, C., Bengio, Y.: Inference for generalisation error. In: Advances in Neural Information Processing 12. MIT Press (2000)"},{"key":"16_CR17","unstructured":"Popelinsky, L., Brazdil, P.: The Principal Components Method as a Preprocessing Stage for Decision Tree Learning. In: Proc. of PKDD Workshop (Data Mining, Decision Support, Meta-learning and ILP). (2000)"},{"key":"16_CR18","doi-asserted-by":"crossref","unstructured":"Sigurdsson, S., Philipsen, P., Hansen, L., Larsen, J., Gniadecka, M., Wulf, H.: Detection of Skin Cancer by Classification of Raman Spectra. IEEE Transactions on Biomedical Engineering 51 (2004)","DOI":"10.1109\/TBME.2004.831538"},{"key":"16_CR19","unstructured":"Popelinsky, L.: Combining the Principal Components Method with Different Learning Algorithms. In: Proc. of ECML\/PKDD IDDM Workshop (Integrating Aspects of Data Mining, Decision Support and Meta-Learning). (2001)"}],"container-title":["Applications and Innovations in Intelligent Systems XIII"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/1-84628-224-1_16.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,21]],"date-time":"2025-01-21T22:45:45Z","timestamp":1737499545000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/1-84628-224-1_16"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[null]]},"ISBN":["9781846282232"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/1-84628-224-1_16","relation":{},"subject":[]}}