IPCA: An interactive system for PCA-based visual analytics.
Jeong, Dong Hyun.
Ziemkiewicz, Caroline.
Fisher, Brian (Brian D.)
Ribarsky, William.
Chang, Remco.
2009.
- Principle Component Analysis (PCA) is a widely used mathematical technique in many fields for factor and trend analysis, dimension reduction, etc. However, it is often considered to be a "black box" operation whose results are difficult to interpret and sometimes counter-intuitive to the user. In order to assist the user in better understanding and utilizing PCA, we have developed a system that ... read morevisualizes the results of principal component analysis using multiple coordinated views and a rich set of user interactions. Our design philosophy is to support analysis of multivariate datasets through extensive interaction with the PCA output. To demonstrate the usefulness of our system, we performed a comparative user study with a known commercial system, SAS/INSIGHT's Interactive Data Exploration. Participants in our study solved a number of high-level analysis tasks with each interface and rated the systems on ease of learning and usefulness. Based on the participants' accuracy, speed, and qualitative feedback, we observe that our system helps users to better understand relationships between the data and the calculated eigenspace, which allows the participants to more accurately analyze the data. User feedback suggests that the interactivity and transparency of our system are the key strengths of our approach. This is the peer reviewed version of the following article: [FULL CITE], which has been published in final form at [Link to final article using the DOI]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.read less
- Jeong, D. H., Ziemkiewicz, C., Fisher, B., Ribarsky, W. and Chang, R. (2009), iPCA: An Interactive System for PCA-based Visual Analytics. Computer Graphics Forum, 28: 767-774. doi:10.1111/j.1467-8659.2009.01475.x
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