This repository was archived by the owner on Aug 15, 2019. It is now read-only.
-
Notifications
You must be signed in to change notification settings - Fork 0
albutko/ml_randomized_optimization
Folders and files
| Name | Name | Last commit message | Last commit date | |
|---|---|---|---|---|
Repository files navigation
Code is available here: https://github.com/albutko/ml_randomized_optimization ## Running My Code This code is based fully on the [ABAGAIL](https://github.com/pushkar/ABAGAIL) repository and has similar build and run instructions as ABAGAIL. ### Requirements * Java 8 * ant ### Instructions 1. Create ABAGAIL.jar * Navigate to the ABAGAIL directory and run ant to build the jar file * `cd ABAGAIL` * `ant` 2. Run Tests within the `ABAGAIL.jar` using java: * In the root directory run the below command to run a specific class * `java -cp ABAGAIL.jar path.to.class` ### Tests There are 4 tests to run in this assignment. Below are the commands of how to run them and their names * NeuralNetClassifierExperiment * `java -cp ABAGAIL.jar exp.tests.NeuralNetClassifierExperiment` * MyFourPeaksTest * `java -cp ABAGAIL.jar exp.tests.MyFourPeaksTest` * MyKnapsackTest * `java -cp ABAGAIL.jar exp.tests.MyKnapsackTest` * MyTravelingSalesmanTest * `java -cp ABAGAIL.jar exp.tests.MyTravelingSalesmanTest` In each of the optimization problems you can change the number of iterations alotted to each algorithm to see performance based on fixed iterations.
About
No description, website, or topics provided.
Resources
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published