Open AccessData Visualization for the Prediction of Liver Cancer Disease using Different Graphical Techniques
Author(s) -
Gururaj L. Kulkarni,
Sanjeev S. Sannakki,
Vijay S. Rajpurohit
Publication year - 2020
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.d8388.049420
Subject(s) - plot (graphics) , visualization , scatter plot , histogram , computer science , box plot , pattern recognition (psychology) , artificial intelligence , graph , data mining , data visualization , image (mathematics) , mathematics , statistics , machine learning , theoretical computer science
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.