{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T14:36:51Z","timestamp":1783521411318,"version":"3.55.0"},"reference-count":36,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2011,11,18]],"date-time":"2011-11-18T00:00:00Z","timestamp":1321574400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/2.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"published-print":{"date-parts":[[2011,12]]},"DOI":"10.1186\/1471-2105-12-450","type":"journal-article","created":{"date-parts":[[2011,11,18]],"date-time":"2011-11-18T02:18:58Z","timestamp":1321582738000},"source":"Crossref","is-referenced-by-count":96,"title":["Random KNN feature selection - a fast and stable alternative to Random Forests"],"prefix":"10.1186","volume":"12","author":[{"given":"Shengqiao","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"E James","family":"Harner","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Donald A","family":"Adjeroh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2011,11,18]]},"reference":[{"key":"5025_CR1","doi-asserted-by":"publisher","DOI":"10.1016\/B0-12-227240-4\/00132-5","volume-title":"Pattern recognition","author":"S Theodoridis","year":"2003","unstructured":"Theodoridis S, Koutroumbas K: Pattern recognition. Academic Press; 2003."},{"key":"5025_CR2","volume-title":"Pattern Classification","author":"RO Duda","year":"2000","unstructured":"Duda RO, Hart PE, Stork DG: Pattern Classification. New York: John Wiley & Sons; 2000."},{"key":"5025_CR3","volume-title":"Bioinformatics","author":"Y Saeys","year":"2007","unstructured":"Saeys Y, Inza I, Larra\u00f1aga P: A review of feature selection techniques in bioinformatics. Bioinformatics 2007., 23(19):"},{"key":"5025_CR4","volume-title":"Classification and Regression Trees","author":"L Breiman","year":"1984","unstructured":"Breiman L, Friedman J, Stone CJ, Olshen R: Classification and Regression Trees. Chapman & Hall\/CRC; 1984."},{"key":"5025_CR5","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman L: Random Forests. Machine Learning 2001, 45: 5\u201332. 10.1023\/A:1010933404324","journal-title":"Machine Learning"},{"key":"5025_CR6","doi-asserted-by":"crossref","first-page":"43","DOI":"10.3233\/IDA-2003-7105","volume":"7","author":"A Al-Ani","year":"2003","unstructured":"Al-Ani A, Deriche M, Chebil J: A new mutual information based measure for feature selection. Intelligent Data Analysis 2003, 7: 43\u201357.","journal-title":"Intelligent Data Analysis"},{"issue":"6-7","key":"5025_CR7","doi-asserted-by":"publisher","first-page":"799","DOI":"10.1016\/S0167-8655(01)00019-8","volume":"22","author":"M Last","year":"2001","unstructured":"Last M, Kandel A, Maimon O: Information-theoretic algorithm for feature selection. Pattern Recognition Letters 2001, 22(6\u20137):799\u2013811. 10.1016\/S0167-8655(01)00019-8","journal-title":"Pattern Recognition Letters"},{"issue":"9","key":"5025_CR8","first-page":"1544","volume":"14","author":"GJ Song","year":"2003","unstructured":"Song GJ, Tang SW, Yang DQ, Wang TJ: A Spatial Feature Selection Method Based on Maximum Entropy Theory. Journal of Software 2003, 14(9):1544\u20131550.","journal-title":"Journal of Software"},{"issue":"3","key":"5025_CR9","doi-asserted-by":"publisher","first-page":"301","DOI":"10.1109\/34.990133","volume":"24","author":"P Mitra","year":"2002","unstructured":"Mitra P, Murthy C, Pal S: Unsupervised feature selection using feature similarity. Pattern Analysis and Machine Intelligence, IEEE Transactions on 2002, 24(3):301\u2013312. 10.1109\/34.990133","journal-title":"Pattern Analysis and Machine Intelligence, IEEE Transactions on"},{"key":"5025_CR10","first-page":"249","volume-title":"ML92: Proceedings of the ninth international workshop on Machine learning","author":"K Kira","year":"1992","unstructured":"Kira K, Rendell LA: A practical approach to feature selection. In ML92: Proceedings of the ninth international workshop on Machine learning. San Francisco, CA: Morgan Kaufmann Publishers Inc; 1992:249\u2013256."},{"key":"5025_CR11","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1023\/A:1008280620621","volume":"7","author":"I Kononenko","year":"1997","unstructured":"Kononenko I, \u0160imec E, Robnik-\u0160ikonja M: Overcoming the Myopia of Inductive Learning Algorithms with RELIEFF. Applied Intelligence 1997, 7: 39\u201355. 10.1023\/A:1008280620621","journal-title":"Applied Intelligence"},{"key":"5025_CR12","first-page":"235","volume-title":"Proceedings of the Twelfth Florida International Artificial Intelligence Research Symposium Conference","author":"MA Hall","year":"1999","unstructured":"Hall MA, Smith LA: Feature Selection for Machine Learning: Comparing a Correlation-based Filter Approach to the Wrapper. In Proceedings of the Twelfth Florida International Artificial Intelligence Research Symposium Conference. Menlo Park, CA: The AAAI Press; 1999:235\u2013239."},{"issue":"5","key":"5025_CR13","doi-asserted-by":"publisher","first-page":"1160","DOI":"10.1021\/ci000384c","volume":"40","author":"D Whitley","year":"2000","unstructured":"Whitley D, Ford M, Livingstone D: Unsupervised Forward Selection: A Method for Eliminating Redundant Variables. Journal of Chemical Information and Computer Science 2000, 40(5):1160\u20131168. 10.1021\/ci000384c","journal-title":"Journal of Chemical Information and Computer Science"},{"key":"5025_CR14","first-page":"1205","volume":"5","author":"L Yu","year":"2004","unstructured":"Yu L, Liu H: Efficient Feature Selection via Analysis of Relevance and Redundancy. The Journal of Machine Learning Research 2004, 5: 1205\u20131224.","journal-title":"The Journal of Machine Learning Research"},{"issue":"1-2","key":"5025_CR15","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1016\/S0004-3702(97)00043-X","volume":"97","author":"R Kohavi","year":"1997","unstructured":"Kohavi R, John GH: Wrappers for feature selection. Artificial Intelligence 1997, 97(1\u20132):273\u2013324. 10.1016\/S0004-3702(97)00043-X","journal-title":"Artificial Intelligence"},{"issue":"1-2","key":"5025_CR16","doi-asserted-by":"publisher","first-page":"245","DOI":"10.1016\/S0004-3702(97)00063-5","volume":"97","author":"A Blum","year":"1997","unstructured":"Blum A, Langley P: Selection of relevant features and examples in machine learning. Artificial Intelligence 1997, 97(1\u20132):245\u2013271. 10.1016\/S0004-3702(97)00063-5","journal-title":"Artificial Intelligence"},{"issue":"6","key":"5025_CR17","doi-asserted-by":"publisher","first-page":"716","DOI":"10.1109\/TAC.1974.1100705","volume":"19","author":"H Akaike","year":"1974","unstructured":"Akaike H: A new look at the statistical model identification. IEEE Transactions on Automatic Control 1974, 19(6):716\u2013723. 10.1109\/TAC.1974.1100705","journal-title":"IEEE Transactions on Automatic Control"},{"issue":"2","key":"5025_CR18","doi-asserted-by":"publisher","first-page":"461","DOI":"10.1214\/aos\/1176344136","volume":"6","author":"G Schwarz","year":"1978","unstructured":"Schwarz G: Estimating the dimension of a model. The Annals of Statistics 1978, 6(2):461\u20134643. 10.1214\/aos\/1176344136","journal-title":"The Annals of Statistics"},{"key":"5025_CR19","doi-asserted-by":"publisher","first-page":"130","DOI":"10.1016\/j.chemolab.2005.09.002","volume":"80","author":"HL Zhai","year":"2006","unstructured":"Zhai HL, Chen XG, Hu ZD: A new approach for the identification of important variables. Chemometrics and Intelligent Laboratory Systems 2006, 80: 130\u2013135. 10.1016\/j.chemolab.2005.09.002","journal-title":"Chemometrics and Intelligent Laboratory Systems"},{"issue":"4","key":"5025_CR20","doi-asserted-by":"publisher","first-page":"952","DOI":"10.1021\/ci050049u","volume":"45","author":"S Li","year":"2005","unstructured":"Li S, Fedorowicz A, Singh H, Soderholm SC: Application of the Random Forest Method in Studies of Local Lymph Node Assay Based Skin Sensitization Data. Journal of Chemical Information and Modeling 2005, 45(4):952\u2013964. 10.1021\/ci050049u","journal-title":"Journal of Chemical Information and Modeling"},{"key":"5025_CR21","volume-title":"BMC Bioinformatics","author":"R D\u00edaz-Uriarte","year":"2006","unstructured":"D\u00edaz-Uriarte R, de Andr\u00e9s SA: Gene selection and classification of microarray data using random forest. BMC Bioinformatics 2006., 7(3):"},{"key":"5025_CR22","volume-title":"BMC Bioinformatics","author":"C Strobl","year":"2007","unstructured":"Strobl C, Boulesteix AL, Zeileis A, Hothorn T: Bias in random forest variable importance measures: Illustrations, sources and a solution. BMC Bioinformatics 2007., 8(25):"},{"key":"5025_CR23","doi-asserted-by":"publisher","first-page":"86","DOI":"10.1093\/bib\/bbq011","volume":"12","author":"ML Calle","year":"2011","unstructured":"Calle ML, Urrea V: Letter to the Editor: Stability of Random Forest importance measures. Briefings in Bioinformatics 2011, 12: 86\u201389. 10.1093\/bib\/bbq011","journal-title":"Briefings in Bioinformatics"},{"key":"5025_CR24","doi-asserted-by":"crossref","unstructured":"Nicodemus KK: Letter to the Editor: On the stability and ranking of predictors from random forest variable importance measures. Briefings in Bioinformatics 12(4):369\u2013373.","DOI":"10.1093\/bib\/bbr016"},{"key":"5025_CR25","volume-title":"PhD thesis","author":"S Li","year":"2009","unstructured":"Li S: Random KNN Modeling and Variable Selection for High Dimensional Data. PhD thesis. West Virginia University; 2009."},{"key":"5025_CR26","volume-title":"Discriminatory Analysis-Nonparametric Discrimination: Consistency Properties","author":"E Fix","year":"1951","unstructured":"Fix E, Hodges J: Discriminatory Analysis-Nonparametric Discrimination: Consistency Properties. 1951. Tech. Rep. 21-49-004, 4, US Air Force, School of Avaiation Medicine"},{"key":"5025_CR27","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1109\/TIT.1967.1053964","volume":"IT-13","author":"T Cover","year":"1967","unstructured":"Cover T, Hart P: Nearest Nieghbor Pattern Classification. IEEE Transaction on Information Theory 1967, IT-13: 21\u201327.","journal-title":"IEEE Transaction on Information Theory"},{"key":"5025_CR28","volume-title":"The Elements of Statistical Learning - Data Mining, Inference, and Prediction","author":"T Hastie","year":"2001","unstructured":"Hastie T, Tibshirani R, Friedman J: The Elements of Statistical Learning - Data Mining, Inference, and Prediction. New York: Springer; 2001. chap. 9, section 2"},{"issue":"10","key":"5025_CR29","first-page":"1","volume":"23","author":"NL Crookston","year":"2007","unstructured":"Crookston NL, Finley AO: yaImpute: An R Package for kNN Imputation. Journal of Statistical Software 2007, 23(10):1\u201316.","journal-title":"Journal of Statistical Software"},{"issue":"6","key":"5025_CR30","doi-asserted-by":"publisher","first-page":"520","DOI":"10.1093\/bioinformatics\/17.6.520","volume":"17","author":"O Troyanskaya","year":"2001","unstructured":"Troyanskaya O, Cantor M, Sherlock G, Brown P, Hastie T, Tibshirani R, Botstein D, Altman RB: Missing value estimation methods for DNA microarrays. Bioinformatics 2001, 17(6):520\u2013525. 10.1093\/bioinformatics\/17.6.520","journal-title":"Bioinformatics"},{"issue":"8","key":"5025_CR31","doi-asserted-by":"publisher","first-page":"832","DOI":"10.1109\/34.709601","volume":"20","author":"TK Ho","year":"1998","unstructured":"Ho TK: The Random Subspace Method for Constructing Decision Forests. IEEE Transactions on Pattern Analysis and Machine Intelligence 1998, 20(8):832\u2013844. 10.1109\/34.709601","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"issue":"4","key":"5025_CR32","first-page":"97","volume":"18","author":"TG Dietterich","year":"1998","unstructured":"Dietterich TG: Machine-Learning Research: Four Current Directions. The AI Magazine 1998, 18(4):97\u2013136.","journal-title":"The AI Magazine"},{"issue":"6","key":"5025_CR33","doi-asserted-by":"publisher","first-page":"2350","DOI":"10.1214\/aos\/1032181158","volume":"24","author":"L Breiman","year":"1996","unstructured":"Breiman L: Heuristics of instability and stabilization in model selection. The Annals of Statistics 1996, 24(6):2350\u20132383.","journal-title":"The Annals of Statistics"},{"key":"5025_CR34","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1007\/BF02295996","volume":"12","author":"Q McNemar","year":"1947","unstructured":"McNemar Q: Note on the sampling error of the difference between correlated proportions or percentages. Psychometrika 1947, 12: 153\u2013157. 10.1007\/BF02295996","journal-title":"Psychometrika"},{"issue":"6","key":"5025_CR35","doi-asserted-by":"publisher","first-page":"1947","DOI":"10.1021\/ci034160g","volume":"43","author":"V Svetnik","year":"2003","unstructured":"Svetnik V, Liaw A, Tong C, Culberson J, Sheridan R, Feuston B: Random Forest: A Classification and Regression Tool for Compound Classification and QSAR Modeling. Journal of Chemical Information and Computer Science 2003, 43(6):1947\u20131958. 10.1021\/ci034160g","journal-title":"Journal of Chemical Information and Computer Science"},{"issue":"474","key":"5025_CR36","doi-asserted-by":"publisher","first-page":"578","DOI":"10.1198\/016214505000001230","volume":"101","author":"Y Lin","year":"2006","unstructured":"Lin Y, Jeon Y: Random Forests and Adaptive Nearest Neighbors. Journal of the American Statistical Association 2006, 101(474):578\u2013590. 10.1198\/016214505000001230","journal-title":"Journal of the American Statistical Association"}],"container-title":["BMC Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/1471-2105-12-450.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1186\/1471-2105-12-450\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/1471-2105-12-450.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,6,19]],"date-time":"2019-06-19T15:42:30Z","timestamp":1560958950000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/1471-2105-12-450"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2011,11,18]]},"references-count":36,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2011,12]]}},"alternative-id":["5025"],"URL":"https:\/\/doi.org\/10.1186\/1471-2105-12-450","relation":{},"ISSN":["1471-2105"],"issn-type":[{"value":"1471-2105","type":"electronic"}],"subject":[],"published":{"date-parts":[[2011,11,18]]},"article-number":"450"}}