Computational Biology Ex3:
By:
1. Yaniv Zimmer 318849908
2. Ben Abraham Nageris 206532533
Link to code (in Github):
https://github.com/BenNageris/CompBioEx3
Intro:
In this project, we solve classification problems using neural networks and genetic algorithms.
We implemented an automatic pipeline to both determine the optimal neural network's architecture (bonus) and its neurpn's weights.
The project solved the suggested classifivcation problems pretty easily and accuratly.
The project was written in Python3.9.
Execution Steps:
1. git clone https://github.com/BenNageris/CompBioEx3
2. Move To Directory: cd <PROJECT_DIRECTORY>\output
3. Execution: <EXECUTOR>.exe
<EXECUTOR> is one of:
3.1.1. build_architecture<0/1>
3.1.2. buildnet<0/1>
3.1.3. runnet<0/1>: runnet<0/1> execution output is to output-testnet<0/1>
for example:
(#) .\build_architecture0.exe
(#) .\build_architecture1.exe
(#) .\buildnet0.exe
(#) .\buildnet1.exe
(#) .\runnet0.exe
(#) .\runnet1.exe
(*) We tested this program on a Windows PC with python3.9 installed.
compbioex3's Introduction
compbioex3's People
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