As the data and number of information sources keeps on mounting, the mining of necessary information and their presentation in a human delicate form becomes a great challenge. Visualization helps us to pictorially represent, evaluate and uncover the knowledge from the data under consideration. Data visualization offers its immense opportunity in the fields of trade, banking, finance, insurance, energy etc. With the data explosion in various fields, there is a large importance for visualization techniques. But when the quantity of data becomes elevated, the visualization methods may take away the competency. Parallel coordinates is an eminent and often used method for data visualization. However the efficiency of this method will be abridged if there are large amount of instances in the dataset, thereby making the visualization clumsier and the data retrieval very inefficient. Here we introduced a data summarization approach as a preprocessing step to the existing parallel coordinate method to make the visualization more proficient. © 2015 Institute of Advanced Engineering and Science. All rights reserved.
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S. S. Kumar, Krishnan, T., S. Ashok, and Dr. M.V. Judy, “Clutter reduction in parallel coordinates using binning approach for improved visualization”, International Journal of Electrical and Computer Engineering, vol. 5, pp. 1564-1568, 2015.