Results 11 to 20 of about 1,780,327 (266)
Categorical Embeddings for Tabular Data using PyTorch [PDF]
ITM Web of Conferences, 2023 Deep learning has received much attention for computer vision and natural language processing, but less for tabular data, which is the most prevalent type of data used in industry.
Khedkar Sanskruti +3 more
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Multivariate Regression Forest for Categorical Attribute Data [PDF]
Jisuanji kexue, 2022 As categorical attributes cannot be utilized directly in some regression models like the linear regression,SVR and most multivariate regression trees,a multivariate split method dealing with multiple types of data is prompted in this paper.We define the ...
LIU Zhen-yu, SONG Xiao-ying
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Learning-Based Dissimilarity for Clustering Categorical Data
Applied Sciences, 2021 Comparing data objects is at the heart of machine learning. For continuous data, object dissimilarity is usually taken to be object distance; however, for categorical data, there is no universal agreement, for categories can be ordered in several ...
Edgar Jacob Rivera Rios +3 more
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Categorical data analysis with Practical Application [PDF]
المجلة العراقية للعلوم الاحصائية, 2009 The main purpose of this study is to find out vectors that can be inserted to the statistical analysis of certain groups of variables which are formed as a result of a certain condition depending on categorical data (i.e. Qualitative variable ).
Furat B. Al-Dassy
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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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, 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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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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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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