Application of classification methods when group sizes are unequal by incorporation of prior probabilities to three common approaches: Application to simulations and mouse urinary chemosignals
暂无分享,去创建一个
R. Brereton | Sarah J. Dixon | Randall R. Reed | Michele L. Schaefer | J. Trevejo | M. Holmboe | Nina Heinrich
[1] Richard G. Brereton,et al. Chemometrics for Pattern Recognition , 2009 .
[2] R. Brereton,et al. Comparison of performance of five common classifiers represented as boundary methods: Euclidean Distance to Centroids, Linear Discriminant Analysis, Quadratic Discriminant Analysis, Learning Vector Quantization and Support Vector Machines, as dependent on data structure , 2009 .
[3] Maria E. Holmboe,et al. Use of cluster separation indices and the influence of outliers: application of two new separation indices, the modified silhouette index and the overlap coefficient to simulated data and mouse urine metabolomic profiles , 2009 .
[4] Fan Gong,et al. Application of dissimilarity indices, principal coordinates analysis, and rank tests to peak tables in metabolomics of the gas chromatography/mass spectrometry of human sweat. , 2007, Analytical chemistry.
[5] Richard G. Brereton,et al. Pattern Recognition of Gas Chromatography Mass Spectrometry of Human Volatiles in Sweat to distinguish the sex of subjects and determine potential Discriminatory Marker Peaks , 2007 .
[6] Reshma Khemchandani,et al. Twin Support Vector Machines for Pattern Classification , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[7] Richard G. Brereton,et al. Applied Chemometrics for Scientists , 2007 .
[8] Yun Xu,et al. Support Vector Machines: A Recent Method for Classification in Chemometrics , 2006 .
[9] B. Lang,et al. Efficient optimization of support vector machine learning parameters for unbalanced datasets , 2006 .
[10] D. Penn,et al. An automated method for peak detection and matching in large gas chromatography‐mass spectrometry data sets , 2006 .
[11] Jan van der Greef,et al. Symbiosis of chemometrics and metabolomics: past, present, and future , 2005 .
[12] Shigeo Abe,et al. Support Vector Machines for Pattern Classification , 1999, Advances in Pattern Recognition.
[13] Richard G. Brereton,et al. Chemometrics: Data Analysis for the Laboratory and Chemical Plant , 2003 .
[14] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[15] Katharina Morik,et al. Combining Statistical Learning with a Knowledge-Based Approach - A Case Study in Intensive Care Monitoring , 1999, ICML.
[16] David B. Dunson,et al. Bayesian Data Analysis , 2010 .
[17] J. Friedman. Regularized Discriminant Analysis , 1989 .
[18] David G. Stork,et al. Pattern Classification , 1973 .
[19] Keinosuke Fukunaga,et al. Introduction to Statistical Pattern Recognition , 1972 .
[20] G. C. Tiao,et al. Bayes's theorem and the use of prior knowledge in regression analysis , 1964 .
[21] R. Fisher. THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS , 1936 .