Book Chapter10.1007/978-3-540-74205-0_121
Parallel Filter: A Visual Classifier Based on Parallel Coordinates and Multivariate Data Analysis
Yonghong Xu,Wenxue Hong,Na Chen,Xin Li,Wenyuan Liu,Tao Zhang +5 more
- 17 Nov 2009
- Vol. 4682, pp 1172-1183
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TL;DR: An interactive visual classification model based on some multivariate graphical presentation is proposed that has the merit of making the invisible visible and users can steer the classification process, consequently favor the understanding and knowledge discovery of original data.
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Abstract: Multivariate visualization techniques are often used as assistant tools for classification tasks up to now. However, few classification systems fully utilize the capability of multivariate visualization and integrate them with multivariate analysis algorithms into a compact system. We propose an interactive visual classification model based on some multivariate graphical presentation in this paper. As an example of it, a visual classifier based on parallel coordinates plot is developed. The multivariate data is first mapped to the parallel coordinates plot, and then an optimizer based on linear discriminant analysis optimizes it into the visualization more fit for classification tasks. This optimized visualization then can be processed by decision tree algorithm and attain classification rules. It has the merit of making the invisible visible and users can steer the classification process, consequently favor the understanding and knowledge discovery of original data.
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Citations
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TL;DR: In this article, the authors proposed a new methodology for machine learning in 2D space (2D ML) in inline coordinates, which is a full machine learning approach that does not require to deal with ndimensional data in n-dimensional space.
11
RfX: A Design Study for the Interactive Exploration of a Random Forest to Enhance Testing Procedures for Electrical Engines
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8
References
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Multivariate data analysis in classification of vegetable oils characterized by the content of fatty acids
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PolyCluster: an interactive visualization approach to construct classification rules
Danyu Liu,Alan P. Sprague,Jeff Gray +2 more
- 16 Dec 2004
TL;DR: A system, called PolyCluster, which adopts state-of-the-art algorithms for data visualization and integrates human domain knowledge into the construction process of classification rules, and can help users to obtain additional knowledge from current datasets.
PaintingClass: interactive construction, visualization and exploration of decision trees
Soon Tee Teoh,Kwan-Liu Ma +1 more
- 24 Aug 2003
TL;DR: This work introduces PaintingClass, a system for interactive construction, visualization and exploration of decision trees, and shows that the user can effectively use PaintingClass to construct a decision tree and explore the decision tree to gain additional knowledge.