Efficient binary embedding of categorical data using BinSketch
Sign Up to like & getrecommendations! Published in 2022 at "Data Mining and Knowledge Discovery"
DOI: 10.1007/s10618-021-00815-y
Abstract: In this work, we present a dimensionality reduction algorithm, aka. sketching, for categorical datasets. Our proposed sketching algorithm Cabin constructs low-dimensional binary sketches from high-dimensional categorical vectors, and our distance estimation algorithm Cham computes a… read more here.
Keywords: embedding categorical; binary embedding; using binsketch; categorical data ... See more keywords
Dealing with categorical data in a multidimensional context: The multidimensional balanced worth.
Sign Up to like & getrecommendations! Published in 2021 at "Social science research"
DOI: 10.1016/j.ssresearch.2021.102561
Abstract: This paper presents an evaluation protocol that permits evaluating the relative performance of a set of populations in a multidimensional context when outcomes are measured in terms of categorical variables. This problem appears in many… read more here.
Keywords: multidimensional context; balanced worth; data multidimensional; dealing categorical ... See more keywords
Go Multivariate: Recommendations on Bayesian Multilevel Hidden Markov Models with Categorical Data.
Sign Up to like & getrecommendations! Published in 2023 at "Multivariate behavioral research"
DOI: 10.1080/00273171.2023.2205392
Abstract: The multilevel hidden Markov model (MHMM) is a promising method to investigate intense longitudinal data obtained within the social and behavioral sciences. The MHMM quantifies information on the latent dynamics of behavior over time. In… read more here.
Keywords: multilevel hidden; categorical data; hidden markov;
Time series analysis of categorical data using auto-odds ratio function
Sign Up to like & getrecommendations! Published in 2018 at "Statistics"
DOI: 10.1080/02331888.2017.1421196
Abstract: ABSTRACT In this paper, we consider the auto-odds ratio function (AORF) as a measure of serial association for a stationary time series process of categorical data at two different time points. Numerical measures such as… read more here.
Keywords: time series; time; function; categorical data ... See more keywords
Using categorical data analyses in determination of dust-related occupational diseases in mining
Sign Up to like & getrecommendations! Published in 2018 at "International Journal of Occupational Safety and Ergonomics"
DOI: 10.1080/10803548.2018.1531535
Abstract: Dust-related occupational diseases are common in the mining sector. It is important to identify employees who have high potential for these diseases and to investigate the factors affecting disease... read more here.
Keywords: occupational diseases; dust related; data analyses; using categorical ... See more keywords
Automatic Fuzzy Clustering Using Non-Dominated Sorting Particle Swarm Optimization Algorithm for Categorical Data
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2927593
Abstract: Categorical data clustering has been attracted a lot of attention recently due to its necessary in the real-world applications. Many clustering methods have been proposed for categorical data. However, most of the existing algorithms require… read more here.
Keywords: fuzzy clustering; automatic fuzzy; categorical data; number clusters ... See more keywords
Graph Enhanced Fuzzy Clustering for Categorical Data Using a Bayesian Dissimilarity Measure
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Fuzzy Systems"
DOI: 10.1109/tfuzz.2022.3189831
Abstract: Categorical data are widely available in many real-world applications, and to discover valuable patterns in such data by clustering is of great importance. However, the lack of a decent quantitative relationship among categorical values makes… read more here.
Keywords: fuzzy clustering; bayesian dissimilarity; categorical data; dissimilarity measure ... See more keywords
From Whole to Part: Reference-Based Representation for Clustering Categorical Data
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Neural Networks and Learning Systems"
DOI: 10.1109/tnnls.2019.2911118
Abstract: Dissimilarity measures play a crucial role in clustering and, are directly related to the performance of clustering algorithms. However, effectively measuring the dissimilarity is not easy, especially for categorical data. The main difficulty of the… read more here.
Keywords: representation; based representation; reference; categorical data ... See more keywords
Rough set based information theoretic approach for clustering uncertain categorical data
Sign Up to like & getrecommendations! Published in 2022 at "PLoS ONE"
DOI: 10.1371/journal.pone.0265190
Abstract: Motivation Many real applications such as businesses and health generate large categorical datasets with uncertainty. A fundamental task is to efficiently discover hidden and non-trivial patterns from such large uncertain categorical datasets. Since the exact… read more here.
Keywords: information; information theoretic; categorical datasets; rough set ... See more keywords
Multi-Objective Evolutionary Rule-Based Classification with Categorical Data
Sign Up to like & getrecommendations! Published in 2018 at "Entropy"
DOI: 10.3390/e20090684
Abstract: The ease of interpretation of a classification model is essential for the task of validating it. Sometimes it is required to clearly explain the classification process of a model’s predictions. Models which are inherently easier… read more here.
Keywords: classification; objective evolutionary; multi objective; rule based ... See more keywords
A Novel Price Prediction Service for E-Commerce Categorical Data
Sign Up to like & getrecommendations! Published in 2023 at "Mathematics"
DOI: 10.3390/math11081938
Abstract: Most e-commerce data include items that belong to different categories, e.g., product types on Amazon and eBay. The accurate prediction of an item’s price on an e-commerce platform will facilitate the maximization of economic benefits… read more here.
Keywords: commerce; regression; prediction; categorical data ... See more keywords