Results 11 to 20 of about 1,081,758 (246)
Equality of opportunity with categorical data
Lecturas de Economía, 2014 This paper refers to some social evaluation problems when equity matters. We propose here a way of assessing the equality of opportunity that is applicable to categorical data.
Carmen Herrero, Antonio Villar
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Clusterability Test for Categorical Data
Knowledge and Information Systems, 2023 28 pages, 12 appendix pages, 17 ...
Lianyu Hu 0001 +4 more
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, 2023 preprint of an Elsevier book chapter, 11 ...
Chen, Dandan, Anderson, Carolyn
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A Memory-Efficient Encoding Method for Processing Mixed-Type Data on Machine Learning
Entropy, 2020 The most common machine-learning methods solve supervised and unsupervised problems based on datasets where the problem’s features belong to a numerical space.
Ivan Lopez-Arevalo +5 more
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Outlier Analysis of Categorical Data using NAVF [PDF]
Informatică economică, 2013 Outlier mining is an important task to discover the data records which have an exceptional behavior comparing with other records in the remaining dataset. Outliers do not follow with other data objects in the dataset.
D. LAKSHMI SREENIVASA REDDY +2 more
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HABOS clustering algorithm for categorical data
工程科学学报, 2016 The clustering algorithm based on sparse feature vector for categorical attributes(CABOSFVC) is an efficient high-dimensional clustering method for categorical data.
WU Sen, JIANG Dan-dan, WANG Qiang
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Categorical Data-Specifications
Theory and Applications of Categories, 1995 Summary: We introduce MD-sketches, which are a particular kind of Finite Sum sketches. Two interesting results about MD-sketches are proved. First, we show that, given two MD-sketches, it is algorithmically decidable whether their model categories are equivalent. Next we show that data-specifications as used in database-design and software engineering,
Piessens, Frank, Steegmans, Eric
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Smoothing Categorical Data [PDF]
, 2012 Global models of a dataset reflect not only the large scale structure of the data distribution, they also reflect small(er) scale structure. Hence, if one wants to see the large scale structure, one should somehow subtract this smaller scale structure from the model. While for some kinds of model --- such as boosted classifiers --- it is easy to see
Siebes, Arno, Kersten, René
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Survey on categorical data for neural networks
Journal of Big Data, 2020 This survey investigates current techniques for representing qualitative data for use as input to neural networks. Techniques for using qualitative data in neural networks are well known.
John T. Hancock, Taghi M. Khoshgoftaar
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