Results 21 to 30 of about 4,674,587 (322)

Clusterwise multivariate regression of mixed-type panel data [PDF]

Statistics and Computing, 2022
Abstract Multivariate panel data of mixed type are routinely collected in many different areas of application, often jointly with additional covariates which complicate the statistical analysis. Moreover, it is often of interest to identify unknown groups of units in a study population using such data structure, i.e., to perform clustering.
Jan Vávra, Arnošt Komárek, Bettina Grün, Gertraud Malsiner‐Walli   +3 more
openalex   +4 more sources

Neuropsychological Assessments of Patients With Acquired Brain Injury: A Cluster Analysis Approach to Address Heterogeneity in Web-Based Cognitive Rehabilitation

Frontiers in Neurology, 2021
We aimed to (1) apply cluster analysis techniques to mixed-type data (numerical and categorical) from baseline neuropsychological standard and widely used assessments of patients with acquired brain injury (ABI) (2) apply state-of-the-art cluster ...
Alejandro García-Rudolph, Alejandro García-Rudolph, Alejandro García-Rudolph, Alberto García-Molina, Alberto García-Molina, Alberto García-Molina, Eloy Opisso, Eloy Opisso, Eloy Opisso, Josep María Tormos, Josep María Tormos, Josep María Tormos, Vince I. Madai, Vince I. Madai, Vince I. Madai, Dietmar Frey, Montserrat Bernabeu, Montserrat Bernabeu, Montserrat Bernabeu   +18 more
doaj   +1 more source

MCF Tree-Based Clustering Method for Very Large Mixed-Type Data Set

IEEE Access, 2021
Several clustering methods have been proposed for analyzing numerous mixed-type data sets composed of numeric and categorical attributes. However, existing clustering methods are not suitable for clustering very large mixed-type data sets because they ...
Hyeong-Cheol Ryu, Sungwon Jung
doaj   +1 more source

Applications of Clustering with Mixed Type Data in Life Insurance

Risks, 2021
Death benefits are generally the largest cash flow items that affect the financial statements of life insurers; some may still not have a systematic process to track and monitor death claims.
Shuang Yin, Guojun Gan, Emiliano A. Valdez, Jeyaraj Vadiveloo   +3 more
doaj   +1 more source

Mixed-type data generation method based on generative adversarial networks

EURASIP Journal on Wireless Communications and Networking, 2022
Data-driven based deep learing has become a key research direction in the field of artificial intelligence. Abundant training data is a guarantee for building efficient and accurate models.
Ning Wei, Longzhi Wang, Guanhua Chen, Yirong Wu, Shunfa Sun, Peng Chen   +5 more
doaj   +1 more source

Designing a Hybrid Equipment-Failure Diagnosis Mechanism under Mixed-Type Data with Limited Failure Samples

Applied Sciences, 2022
The rarity of equipment failures results in a high level of imbalance between failure data and normal operation data, which makes the effective classification and prediction of such data difficult.
Cheng-Hui Chen, Chen-Kun Tsung, Shyr-Shen Yu   +2 more
doaj   +1 more source

BCBimax Biclustering Algorithm with Mixed-Type Data [PDF]

JUITA : Jurnal Informatika
The application of biclustering analysis to mixed data is still relatively new. Initially, biclustering analysis was primarily used on gene expression data that has an interval scale. In this research, we will transform ordinal categorical variables into interval scales using the Method of Successive Interval (MSI).
Hanifa Izzati, Indahwati Indahwati, Anik Djuraidah   +2 more
openalex   +3 more sources

Model Based Clustering for Mixed Data: clustMD [PDF]

, 2015
A model based clustering procedure for data of mixed type, clustMD, is developed using a latent variable model. It is proposed that a latent variable, following a mixture of Gaussian distributions, generates the observed data of mixed type.
Gormley, Isobel Claire, McParland, Damien   +1 more
core   +3 more sources

A real data-driven simulation strategy to select an imputation method for mixed-type trait data.

PLoS Computational Biology, 2023
Missing observations in trait datasets pose an obstacle for analyses in myriad biological disciplines. Considering the mixed results of imputation, the wide variety of available methods, and the varied structure of real trait datasets, a framework for ...
Jacqueline A May, Zeny Feng, Sarah J Adamowicz   +2 more
doaj   +1 more source

A Novel Attention-Based Multi-Modal Modeling Technique on Mixed Type Data for Improving TFT-LCD Repair Process

IEEE Access, 2022
In Thin-Film Transistor Liquid-Crystal Display (TFT-LCD) manufacturing, conducting a machine learning based system with multiple data types has become actively desired to solve complicated problems.
Yi Liu, Hsueh-Ping Lu, Ching-Hao Lai
doaj   +1 more source