Data Visualization for the Prediction of Liver Cancer Disease using Different Graphical Techniques
Gururaj L Kulkarni1, Sanjeev S Sannakki2, Vijay S Rajpurohit3
1Gururaj Kulkarni*, Assistant Professor, Department of Information Science and Engineering, Gogte Institute of Technology, Belgaum, Karnataka, India.
2Dr. Sanjeev S Sannakki, Professor, Department of Computer Science and Engineering, Gogte Institute of Technology, Belgaum.
3Dr.Vijay S Rajpurohit, Professor, Department of Computer Science and Engg, KLS Gogte Institute of Technology , Belagavi, Karnataka, India
Manuscript received on March 28, 2020. | Revised Manuscript received on April 25, 2020. | Manuscript published on April 30, 2020. | PP: 1893-1895 | Volume-9 Issue-4, April 2020. | Retrieval Number: D8388049420/2020©BEIESP | DOI: 10.35940/ijeat.D8388.049420
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Data visualization is the technique for analyzing the data from the collected dataset. Different plots can be drawn for the data visualization. Microscopic images of the liver are being collected as a dataset from the authorized laboratory and the Joint plot, Violin plot and distribution plot are applied on them for the analysis which helps to extract the specific features and for the classification. Joint plot uses the scatter plot and Histogram technique in order to visualize the data. Violin plot technique is used for plotting the numeric data which helps in gray level co-occurrence matrix. Distribution graph is plotted to check the distribution of tones captured in the image so that we can differentiate based on the tones. All three graphs plotted extract the different features which help in efficient analysis.
Keywords: Dataset, Data visualization, Joint plot, Violin plot, Distribution plot.