Khiops CoViz: A Tool for Visual Exploratory Analysis of K-Coclustering Results
Abstract
Identifying and visually analyzing interesting interactions between variables in large-scale data sets through k -coclustering is of high importance. We present Khiops CoViz^1, a tool for visual analysis of interesting relationships between two or more variables (categorical and/or numerical). The visualization of k variables coclustering takes the form of a grid/matrix whose dimensions are partitioned: categorical variables are grouped into clusters and numerical variables are discretized. The tool allows several kinds of visualization at various scales for grid representation of coclustering results by means of several criteria each of which providing different insights into the data. Hereafter, several screen shots describe the main visual components of the tool.
Cite
Text
Guerraz et al. "Khiops CoViz: A Tool for Visual Exploratory Analysis of K-Coclustering Results." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2014. doi:10.1007/978-3-662-44845-8_31Markdown
[Guerraz et al. "Khiops CoViz: A Tool for Visual Exploratory Analysis of K-Coclustering Results." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2014.](https://mlanthology.org/ecmlpkdd/2014/guerraz2014ecmlpkdd-khiops/) doi:10.1007/978-3-662-44845-8_31BibTeX
@inproceedings{guerraz2014ecmlpkdd-khiops,
title = {{Khiops CoViz: A Tool for Visual Exploratory Analysis of K-Coclustering Results}},
author = {Guerraz, Bruno and Boullé, Marc and Gay, Dominique and Clérot, Fabrice},
booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
year = {2014},
pages = {444-447},
doi = {10.1007/978-3-662-44845-8_31},
url = {https://mlanthology.org/ecmlpkdd/2014/guerraz2014ecmlpkdd-khiops/}
}