This application displays n-Dimensional data in 2D using General Line Coordinates Linear (GLC-L) then visualizes the results as Hyper Blocks using CUDA for optimization.
- For better class separation, Linear Discriminant Analysis (LDA) is used to get the optimal angles and threshold for a visualization.
- Adjustments to the angles and threshold can be done by using the related slider.
- Graphs produced by this program can be panned, zoomed in/out, and scaled.
- Graph order can be rearranged.
- Analytics generated by this program include the "All Data," "Data Without Overlap," "Overlap Data," and "Worst Case," confusion matrices as well as k-fold cross validation.
Please refer to the user manual for specifics on any of the information above.
- Dataset must be in .csv format
- Dataset must include a header row
- If there is an ID column, it must be first
- If there is a class column it must be last
- Dataset features besides "class" must be numeric
- Java 17 - download
- Windows
- Clone repository and open in explorer
- Open "run" directory
- Unzip DV.zip
- Run "DV.exe"
- Follow instructions in "Run Instructions" for additional help
- Clone repository and open as project in Intellij IDE
- Build project
- Run
- Clone repository
- Run from root directory to compile:
javac -cp "lib/*:src" src/*.java src/Sliders/*.java - Run from root directory to run:
java -cp "lib/*:src" Main
This method requires the use of the lib directory for libraries, this can be manually updated to fit your system should a specific dependency version be required.
This project is licensed under the MIT License for both personal and commercial use. See the LICENSE file for details.