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External Logistic Biplots for Mixed Types of Data
2020A simultaneous representation of individuals and variables in a data matrix is called a biplot. When variables are binary, nominal, or ordinal, a classical linear biplot representation is not adequate. Recently, biplots for categorical data-based logistic response models have been proposed.
José L. Vicente-Villardón +1 more
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Unsupervised evolutionary clustering algorithm for mixed type data
IEEE Congress on Evolutionary Computation, 2010In this paper, we propose a novel unsupervised evolutionary clustering algorithm for mixed type data, evolutionary k-prototype algorithm (EKP). As a partitional clustering algorithm, k-prototype (KP) algorithm is a well-known one for mixed type data. However, it is sensitive to initialization and converges to local optimum easily.
Zhi Zheng +4 more
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Distance function for mixed type data
2007There are several strategies to cope with the simultaneous presence of different measurement scales. A reasonable option would be to compute the dissimilarity matrix for each type of variable: bynary, categorical, ordinal and metric. Then a compromise dissimilarity matrix can be achieved by using a convex combination of all the partial matrices ...
TARSITANO, Agostino, Bonafine I.
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Clustering bivariate mixed-type data via the cluster-weighted model
Computational Statistics, 2015zbMATH Open Web Interface contents unavailable due to conflicting licenses.
PUNZO, ANTONIO, INGRASSIA, Salvatore
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K-Centers Algorithm for Clustering Mixed Type Data
2007The K-modes and K-prototypes algorithms both apply the frequency-based update method for centroids, regarding attribute values with the highest frequency but neglecting other attribute values, which affects the accuracy of clustering results. To solve this problem, the K-centers clustering algorithm is proposed to handle mixed type data.
Wei-Dong Zhao +2 more
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k-SubMix: Common Subspace Clustering on Mixed-Type Data
2023Klein, Mauritius +2 more
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An overview of real‐world data sources for oncology and considerations for research
Ca-A Cancer Journal for Clinicians, 2022Lynne Penberthy +2 more
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Unsupervised Classification for Skewed and Mixed-Type Data
2023Clustering, also known as unsupervised classification, is a foundational machine learning technique and is used to find underlying group structures in data. There are many well-established model-based techniques to analyze either categorical or continuous data in the clustering paradigm. However, there is a relative paucity of work for mixed-type data,
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Interferon gamma constrains type 2 lymphocyte niche boundaries during mixed inflammation
Immunity, 2022Kelly M Cautivo +2 more
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Innovations in research and clinical care using patient‐generated health data
Ca-A Cancer Journal for Clinicians, 2020H S L Jim +2 more
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