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ActiveLearningProj

query_strategies modify the active learning strategies to serve a streaming pool

How to run this project experiments

simple_linreg_exp.py is the experiment for linear regression. Specify parameters as follows:

-n := num_rounds (default = 10)
-c := num_coeffs (default = 5)
-s := initial_sample_sz (default = 20)
-p := pool_sz (default = 1000)
-b := budget (default = 10)
-i := iter_per_algo (default = 10)
-v := verbose mode (default = false)
-m := flag to turn on measurement error (default=false)

Example run command:

python3 simple_linreg_exp.py -n 1000 -c 2 -b 1 -p 1000 -i 25

logreg_experiment.py recreates our results for the logistic regression experiement. Example run command:

python3 logreg_experiment.py

multivar-exp.py is the experiment for multiple linear regression. Specify parameters as follows:

-c := num_coeffs (default = 5)
-m := flag to turn on measurement error (default=false)
-v := verbose mode (default = false)

Example run command:

python3 multivar-exp.py -c 5

Developer's Corner:

Contributing Summary

  • To format code, run black .
  • To lint code, run flake8 .
  • To install requirements, run pip install -r requirements.txt

Contributing

  1. Fork this Repo
  2. Clone the Repo onto your computer -- You may need to setup an SSH Key on your device.
  • Run pip install -r requirements.txt to get all the packages you need.
  1. Create a branch (git checkout -b new-feature)
  2. Make Changes
  3. Run necessary quality assurance tools
  1. Add your changes (git commit -am "Commit Message" or git add <whatever files/folders you want to add> followed by git commit -m "Commit Message")
  2. Push your changes to the repo (git push origin new-feature)
  3. Create a pull request

Code Quality Tools

black formatter automatically formats code

  1. Run pip install black to get the package.
  2. After making changes, run black ./.

flake8 lints code

Notifies you if any code is not currently up to Python standards.

  1. Run pip install flake8 to get the package.
  2. After making changes, run flake8.

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Active Learning Experiment

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