This small tool, Single Variable View svVu was developed for in-depth data analysis on single feature (attribute) variable as a part of research collaboration work with research team in School of Computer Science, Edith Cowan University, Western Australia.
Functionalities of this tool;
1. Loading N-dimensional data files,
2. Selecting one of the N-dimension features,
3. Selecting one of the data distribution function types (Gaussian Normal Distribution by default),
4. (‘View’ button) Plotting distribution functions for each selected feature w.r.t. all the output decision classes,
5. Showing the “membership values (closeness / belonging degrees)” of a new unknown input value within [min max] range (‘Analyze’ button),
6. Displaying statistics of the selected feature variable,
7. Calculating overlap degrees of distribution of the selected feature variable w.r.t. its output classes,
8. Calculating SNR (Signal-to-Noise Ratio) for the selected feature to show how much its output groups are separated from each other,
9. Calculating membership degrees for the unknown ‘test’ N-dimensional data points and Generating the list of rank on those unknown test data set.
Even though this is a small tool for data analysis, it has achieved a significant part of the research for in-depth data analysis.