Model-based approach for household clustering with mixed scale variables
نویسندگان
چکیده
منابع مشابه
Fuzzy clustering algorithms for mixed feature variables
This paper presents fuzzy clustering algorithms for mixed features of symbolic and fuzzy data. El-Sonbaty and Ismail proposed fuzzy c-means (FCM) clustering for symbolic data and Hathaway et al. proposed FCM for fuzzy data. In this paper we give a modi3ed dissimilarity measure for symbolic and fuzzy data and then give FCM clustering algorithms for these mixed data types. Numerical examples and ...
متن کاملA partition-based algorithm for clustering large-scale software systems
Clustering techniques are used to extract the structure of software for understanding, maintaining, and refactoring. In the literature, most of the proposed approaches for software clustering are divided into hierarchical algorithms and search-based techniques. In the former, clustering is a process of merging (splitting) similar (non-similar) clusters. These techniques suffered from the drawba...
متن کاملModel based clustering for mixed data: clustMD
Amodel 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. The observed data may be any combination of continuous, binary, ordinal or nominal variables. clustMD employs a parsimonious covariance structure for the lat...
متن کاملClustering of samples and variables with mixed-type data
Analysis of data measured on different scales is a relevant challenge. Biomedical studies often focus on high-throughput datasets of, e.g., quantitative measurements. However, the need for integration of other features possibly measured on different scales, e.g. clinical or cytogenetic factors, becomes increasingly important. The analysis results (e.g. a selection of relevant genes) are then vi...
متن کاملScale-based approach to hierarchical fuzzy clustering
Sensorial signals are processed by brain by relying on their signi"cant aspects. Fuzzy and scale-based approaches try to imitate this mechanism. In the paper, a new clustering algorithm is proposed which makes use of both approaches. It is characterised by a hierarchical splitting process guided by the scale-based approach and based on the repetitive application of an improved version of the Mi...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Advances in Data Analysis and Classification
سال: 2018
ISSN: 1862-5347,1862-5355
DOI: 10.1007/s11634-018-0313-6