Abstract

In this paper I analysis about the visualization techniques of large set of data with parallel coordinates. Parallel Coordinate is an interesting method which can be widely used throughout the world, not only at research area but also other field such as business, market, finance and so on. The aim of this research work is to implement Parallel Coordinate and refinements to Parallel Coordinates using curve. In parallel coordinates visualization of data set is performed by using straight lines. Then lines replaced with the collection of smooth curves across the attribute axis, allowing individual data element to be traced under certain limitations normally impossible due to “Crossing Problem” .Then the notion of spreading out points on axis with few discrete value is introduced, which leads to a simple filter technique when the user selects value on such axis. In this paper I proposed a new concept of visualization of large set of data with parallel Coordinate. Parallel coordinates were proposed by Alfred Inselberg as a new way to represent multidimensional information. A parallel coordinate’s visualization assigns one vertical axis to each variable, and evenly spaces these axes horizontally. This is in contrast to the traditional Cartesian coordinates system where all axes are mutually perpendicular. By drawing the axes parallel to one another, one can represent data in much greater than three dimensions. Each variable is plotted on its own axis, and the values of the variables on adjacent axes are connected by straight lines. Thus, a point in an n-dimensional space becomes a polygonal line laid out across the n parallel axes with n-1 line segments connecting the n data values. In this way, the search for relations among the variables is transformed into a 2-D pattern recognition problem, and the variables become amenable to visualization.

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