{"main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2001/LoDuHa01.pdf","open_access":"1"}],"language":[{"iso":"eng"}],"type":"journal_article","date_updated":"2022-01-06T06:51:11Z","publication":"IEEE Transactions on Pattern Analysis and Machine Intelligence","author":[{"first_name":"M.","full_name":"Loog, M.","last_name":"Loog"},{"last_name":"Duin","full_name":"Duin, R.P.W.","first_name":"R.P.W."},{"full_name":"Haeb-Umbach, Reinhold","last_name":"Haeb-Umbach","id":"242","first_name":"Reinhold"}],"year":"2001","status":"public","intvolume":"        23","user_id":"44006","citation":{"chicago":"Loog, M., R.P.W. Duin, and Reinhold Haeb-Umbach. “Multiclass Linear Dimension Reduction by Weighted Pairwise Fisher Criteria.” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i> 23, no. 7 (2001): 762–66. <a href=\"https://doi.org/10.1109/34.935849\">https://doi.org/10.1109/34.935849</a>.","short":"M. Loog, R.P.W. Duin, R. Haeb-Umbach, IEEE Transactions on Pattern Analysis and Machine Intelligence 23 (2001) 762–766.","bibtex":"@article{Loog_Duin_Haeb-Umbach_2001, title={Multiclass linear dimension reduction by weighted pairwise Fisher criteria}, volume={23}, DOI={<a href=\"https://doi.org/10.1109/34.935849\">10.1109/34.935849</a>}, number={7}, journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, author={Loog, M. and Duin, R.P.W. and Haeb-Umbach, Reinhold}, year={2001}, pages={762–766} }","apa":"Loog, M., Duin, R. P. W., &#38; Haeb-Umbach, R. (2001). Multiclass linear dimension reduction by weighted pairwise Fisher criteria. <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, <i>23</i>(7), 762–766. <a href=\"https://doi.org/10.1109/34.935849\">https://doi.org/10.1109/34.935849</a>","ieee":"M. Loog, R. P. W. Duin, and R. Haeb-Umbach, “Multiclass linear dimension reduction by weighted pairwise Fisher criteria,” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, vol. 23, no. 7, pp. 762–766, 2001.","ama":"Loog M, Duin RPW, Haeb-Umbach R. Multiclass linear dimension reduction by weighted pairwise Fisher criteria. <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>. 2001;23(7):762-766. doi:<a href=\"https://doi.org/10.1109/34.935849\">10.1109/34.935849</a>","mla":"Loog, M., et al. “Multiclass Linear Dimension Reduction by Weighted Pairwise Fisher Criteria.” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, vol. 23, no. 7, 2001, pp. 762–66, doi:<a href=\"https://doi.org/10.1109/34.935849\">10.1109/34.935849</a>."},"volume":23,"_id":"11870","title":"Multiclass linear dimension reduction by weighted pairwise Fisher criteria","department":[{"_id":"54"}],"issue":"7","page":"762-766","doi":"10.1109/34.935849","abstract":[{"lang":"eng","text":"We derive a class of computationally inexpensive linear dimension reduction criteria by introducing a weighted variant of the well-known K-class Fisher criterion associated with linear discriminant analysis (LDA). It can be seen that LDA weights contributions of individual class pairs according to the Euclidean distance of the respective class means. We generalize upon LDA by introducing a different weighting function"}],"oa":"1","date_created":"2019-07-12T05:29:51Z","keyword":["approximate pairwise accuracy","Bayes error","Bayes methods","error statistics","Euclidean distance","Fisher criterion","linear dimension reduction","linear discriminant analysis","pattern classification","statistical analysis","statistical pattern classification","weighting function"]}