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A comparison of the performance of threshold criteria for binary classification in terms of predicted prevalence and kappaFREEMAN, Elizabeth A; MOISEN, Gretchen G.Ecological modelling. 2008, Vol 217, Num 1-2, pp 48-58, issn 0304-3800, 11 p.Article

On measuring the performance of binary classifiersPARKER, Charles.Knowledge and information systems (Print). 2013, Vol 35, Num 1, pp 131-152, issn 0219-1377, 22 p.Article

Accurate on-line v-support vector learningBIN GU; WANG, Jian-Dong; YU, Yue-Cheng et al.Neural networks. 2012, Vol 27, pp 51-59, issn 0893-6080, 9 p.Article

The data complexity index to construct an efficient cross-validation methodLI, Der-Chiang; FANG, Yao-Hwei; FANG, Y. M. Frank et al.Decision support systems. 2010, Vol 50, Num 1, pp 93-102, issn 0167-9236, 10 p.Article

C459. On improving the binary classification accuracy of the quadratic discriminantLEE, S. S.Journal of statistical computation and simulation (Print). 2002, Vol 72, Num 1, pp 3-5, issn 0094-9655, 3 p.Article

Learning to classify with missing and corrupted featuresDEKEL, Ofer; SHAMIR, Ohad; LIN XIAO et al.Machine learning. 2010, Vol 81, Num 2, pp 149-178, issn 0885-6125, 30 p.Article

Orthogonality-based label correction in multi-class classificationXUE, H; CHEN, S.Electronics letters. 2013, Vol 49, Num 12, pp 754-756, issn 0013-5194, 3 p.Article

Rapid octree construction from image sequencesSZELISKI, R.CVGIP. Image understanding. 1993, Vol 58, Num 1, pp 23-32, issn 1049-9660Article

A new decision to take for cost-sensitive Naïve Bayes classifiersDI NUNZIO, Giorgio Maria.Information processing & management. 2014, Vol 50, Num 5, pp 653-674, issn 0306-4573, 22 p.Article

Improved methods for bandwidth selection when estimating ROC curvesHALL, Peter G; HYNDMAN, Rob J.Statistics & probability letters. 2003, Vol 64, Num 2, pp 181-189, issn 0167-7152, 9 p.Article

In Silico Binary Classification QSAR Models Based on 4D-Fingerprints and MOE Descriptors for Prediction of hERG BlockageSU, Bo-Han; SHEN, Meng-Yu; ESPOSITO, Emilio Xavier et al.Journal of chemical information and modeling. 2010, Vol 50, Num 7, pp 1304-1318, issn 1549-9596, 15 p.Article

Density weighted support vector data descriptionMYUNGRAEE CHA; JUN SEOK KIM; BAEK, Jun-Geol et al.Expert systems with applications. 2014, Vol 41, Num 7, pp 3343-3350, issn 0957-4174, 8 p.Article

Extension of a Kernel-Based Classifier for Discriminative Spoken Keyword SpottingTABIBIAN, Shima; AKBARI, Ahmad; NASERSHARIF, Babak et al.Neural processing letters. 2014, Vol 39, Num 2, pp 195-218, issn 1370-4621, 24 p.Article

Fuzzy MaxGWMA chart for identifying abnormal variations of on-line manufacturing processes with imprecise informationSHU, Ming-Hung; NGUYEN, Thanh-Lam; HSU, Bi-Min et al.Expert systems with applications. 2014, Vol 41, Num 4, pp 1342-1356, issn 0957-4174, 15 p., 1Article

Group sparse reconstruction for image segmentationXIAOQIANG LU; XUELONG LI.Neurocomputing (Amsterdam). 2014, Vol 136, pp 41-48, issn 0925-2312, 8 p.Article

Kernel learning at the first level of inferenceCAWLEY, Gavin C; TALBOT, Nicola L. C.Neural networks. 2014, Vol 53, pp 69-80, issn 0893-6080, 12 p.Article

Multicategory large margin classification methods: Hinge losses vs. coherence functionsZHIHUA ZHANG; CHENG CHEN; GUANG DAI et al.Artificial intelligence (General ed.). 2014, Vol 215, pp 55-78, issn 0004-3702, 24 p.Article

The BeiHang Keystroke Dynamics Systems, Databases and baselinesJUAN LIU; BAOCHANG ZHANG; HAORAN ZENG et al.Neurocomputing (Amsterdam). 2014, Vol 144, pp 271-281, issn 0925-2312, 11 p.Article

Fault detection based on a robust one class support vector machineSHEN YIN; XIANGPING ZHU; CHEN JING et al.Neurocomputing (Amsterdam). 2014, Vol 145, pp 263-268, issn 0925-2312, 6 p.Article

Diversity measures for one-class classifier ensemblesKRAWCZYK, Bartosz; WOZNIAK, Michał.Neurocomputing (Amsterdam). 2014, Vol 126, pp 36-44, issn 0925-2312, 9 p.Conference Paper

Multiobjective genetic programming for maximizing ROC performancePU WANG; KE TANG; WEISE, Thomas et al.Neurocomputing (Amsterdam). 2014, Vol 125, pp 102-118, issn 0925-2312, 17 p.Conference Paper

Operator functional state classification using least-square support vector machine based recursive feature elimination techniqueZHONG YIN; JIANHUA ZHANG.Computer methods and programs in biomedicine (Print). 2014, Vol 113, Num 1, pp 101-115, issn 0169-2607, 15 p.Article

A fuzzy binary neural network for interpretable classificationsMEYER, Robert; O'KEEFE, Simon.Neurocomputing (Amsterdam). 2013, Vol 121, pp 401-415, issn 0925-2312, 15 p.Article

Computational intelligence for heart disease diagnosis: A medical knowledge driven approachNAHAR, Jesmin; IMAM, Tasadduq; TICKLE, Kevin S et al.Expert systems with applications. 2013, Vol 40, Num 1, pp 96-104, issn 0957-4174, 9 p.Article

Exploring Monaural Features for Classification-Based Speech SegregationYUXUAN WANG; KUN HAN; DELIANG WANG et al.IEEE transactions on audio, speech, and language processing. 2013, Vol 21, Num 1-2, pp 270-279, issn 1558-7916, 10 p.Article

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