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Artificial Neural Networks

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code
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figures
figures
 
 
report
report
 
 
HW4_Student.pdf
HW4_Student.pdf
 
 
README.md
README.md
 
 

README.md

Implements Classification (Binary & Multi-Class) for Artificial Neural Networks using the Batch Gradient Descent algorithm. Precision vs Recall graph is visualized in part2.m.

Organization

  • This folder contains code(+data), figures, and report in respective folders for the Assignment Specification in HW_4 Student

Source Code

  • The folder contains part1.m, part2.m, part3.m , ann1.dat (DATA), ann2.dat (DATA) as part of the source code for respective parts of the assignment
  • CTG.csv, spambase.data are the actual data files
  • Although the code will work even if the data files are not present, it is still included here for convenience

Figures

  • part1.jpg, part2.jpg, part3.jpg are visualization graphs for the respective parts of the assignment

Report

  • aisraney_hw4_report.pdf is the final solution report

Matlab Version

  • The version of matlab used here is r2016b (Drexel software)

Instructions for Drexel's Tux cluster

  • cd into the directory
  • type in matlab -r "run part4.m"