Details Details PDF BIBTEX RIS Title Discretization of data using Boolean transformations and information theory based evaluation criteria Journal title Bulletin of the Polish Academy of Sciences Technical Sciences Yearbook 2015 Volume 63 Issue No 4 Authors Jankowski, C. ; Reda, D. ; Mańkowski, M. ; Borowik, G. Divisions of PAS Nauki Techniczne Coverage 923-932 Date 2015[2015.01.01 AD - 2015.12.31 AD] Identifier DOI: 10.1515/bpasts-2015-0105 ; ISSN 2300-1917 Source Bulletin of the Polish Academy of Sciences: Technical Sciences; 2015; 63; No 4; 923-932 References Kohavi (1995), The power of decision tables :, Machine Learning ECML, 912, doi.org/10.1007/3-540-59286-557 ; Frank (1999), Making better use of global discretization Sixteenth on, Proc Int Machine Learning, 1. ; Ekbal (2006), Improvement of prediction accuracy using discretization and voting classifier th on Pattern Recognition, Int, 18, doi.org/10.1109/ICPR.2006.698 ; Borowik (2014), Fast algorithm of attribute reduction based on the complementation of Boolean function Advanced Methods and Applications in Computational, Intelligence, 1, doi.org/10.1007/978-3-319-01436-42 ; Lustgarten (2011), Application of an efficient Bayesian discretization method to biomedical data, BMC Bioinformatics, 12, doi.org/10.1186/1471-2105-12-309 ; Grzymala (2013), Discretization based on entropy and multiple scanning, Entropy, 15, 1486, doi.org/10.3390/e15051486 ; Platt (1999), Fast training of support vector machines using sequential minimal optimization Advances in Kernel, Methods, 1. ; Augasta (2012), A new discretization algorithm based on range coefficient of dispersion and skewness for neural networks classifier, Applied Soft Computing, 12, 619, doi.org/10.1016/j.asoc.2011.11.001 ; Žádník (2009), Is spam visible in flow - level statistics ? CESNET National Research and Education Network Rep, Tech. ; Borowik (2013), Boolean function complementation based algorithm for data discretization Systems - in, Computer Aided Theory EUROCAST Lecture Notes Computer Science, 8112, doi.org/10.1007/978-3-642-53862-928 ; Moraga (2007), Design of neural networks th Knowledge - Based Intelligent Informational and Engineering Systems in, Int Lecture Notes Computer Science, 4692, doi.org/10.1007/978-3-540-74819-94 ; Hui (2014), Discrete Fourier transform based pattern classifiers Bull, Tech, 15, doi.org/10.2478/bpasts-2014-0002 ; Cessie (1992), van Houwelingen Ridge estimators in logistic regression, Applied Statistics, 41, 191, doi.org/10.2307/2347628 ; Fayyad (1996), From data mining to knowledge discovery in databases, AI Magazine, 17. ; Mangasarian (1990), Cancer diagnosis via linear programming, SIAM News, 23, 1. ; Shehzad (2012), Edisc : a class - tailored discretization technique for rule - based classification Knowledge and Data, IEEE Trans Engineering, 24, 1435, doi.org/10.1109/TKDE.2011.101 ; Liu (2002), Discretization : An enabling technique Mining and Knowledge, Data Discovery, 6, 393, doi.org/10.1023/A:1016304305535 ; Cuingnet (2011), Automatic classification of patients with Alzheimer s disease from structural MRI : a comparison of ten methods using the ADNI database, NeuroImage, 56, 766, doi.org/10.1016/j.neuroimage.2010.06.013 ; Jastriebow (2014), Analysis of multi - step algorithms for cognitive maps learning, Bull Tech, 735, doi.org/10.2478/bpasts-2014-0079 ; Steinbach (2011), Improvements of the construction of exact minimal covers of Boolean functions Systems - in, Computer Aided Theory EUROCAST Lecture Notes Computer Science, 6928, doi.org/10.1007/978-3-642-27579-135 ; Nguyen (2014), ohm Unsupervised interaction - preserving discretization of multivariate data Mining and Knowledge, Data Discovery, 28, 1366, doi.org/10.1007/s10618-014-0350-5 ; Maslove (2013), Discretization of continuous features in clinical datasets American, Medical Informatics Association, 20, 544, doi.org/10.1136/amiajnl-2012-000929 ; Chaudhari (2014), Discretization of temporal data : a survey Computer and, Science Information Security, 11, 66. ; Breiman (2001), Random forests, Machine Learning, 45, 5, doi.org/10.1023/A:1010933404324 ; Raghuvanshi (2011), Image processing and machine learning for the diagnosis of melanoma cancer on Biomedical Electronics and Devices, BIODEVICES Proc, 1. ; Holmes (1994), Weka : a machine learning workbench Second Australian and New Zealand Conf Intelligent, Proc Information Systems, 1, doi.org/10.1109/ANZIIS.1994.396988