vinceduarte / hipergator

CIS6930

hipergator

CIS6930

Dependencies

• Anaconda https://docs.anaconda.com/anaconda/install/linux/

  Install using the GUI application bash ~/Downloads/Anaconda3-2021.05-Linux-x86_64.sh

  Initialize: source <path to conda>/bin/activate conda init

• Virtual enviornment https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&cad=rja&uact=8&ved=2ahUKEwi7v87dl7bzAhVDTTABHdn4CeUQFnoECAsQAQ&url=https%3A%2F%2Fdocs.python.org%2F3%2Flibrary%2Fvenv.html&usg=AOvVaw1SQ6VGTcJCX7W6wOs1SpnV

  1. Using Anaconda https://uoa-eresearch.github.io/eresearch-cookbook/recipe/2014/11/20/conda/ Create the virtual enviornment if it does not exist: conda create -n yourenvname python=x.x anaconda

     Activate the virtual enviornment in terminal: conda activate venv If done correctly, (venv) will show in the terminal.

     Deactivate the virtual enviornment: conda deactivate venv

     Remove the virtual enviornment if you need a new one: conda remove -n venv -all

  2. Using python out of the box Create the virtual enviornment if it does not exist: python3 -m venv ./venv

     Activate the virtual enviornment in terminal: source /path/to/venv/bin/activate If done correctly, (venv) will show in the terminal.

     Deactivate the virtual enviornment: deactivate .venv

     Remove the virtual enviornment if you need a new one: sudo rm -rf venv

  Install dependencies:

  • PyTorch-1.8.1 CPU ONLY conda install pytorch==1.8.1 torchvision==0.9.0 torchaudio==0.8.0 cpuonly -c pytorch

• Matplotlib https://matplotlib.org/stable/users/installing.html

• scikit-learn https://scikit-learn.org/stable/install.html

TODO: Need to Add (Code):

• Return prediction for a given input
• Check for overfitting !!!!!!
• ~~Support for multilabel and final
• Integration for HiperGator
• ~~Integration for game
• Accuracy Part II (Since this is really a multi-label classification problem that is being treated as a regression problem, please report the accuracy of the multi-label regressor as if it were a classifier, by rounding the output of each regression output to either 0 or 1 and comparing with the testing data) Must write up:
• Classifier and Regression Analysis (see bolded section)
• Written Report
• Video!