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

[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 .