Probabilistic Linear Discriminant Analysis
This model was written for an Explainable Artificial Intelligence (XAI) project, so it stores a bunch of parameters in memory that are not necessary for simple classification problems.
conda env create -f environment.yml -n plda # "plda" is the environment name.
- If you have one,
activate your conda envrionment with
conda activate plda.
- Move this repository to the appropriate directory. This might be a modules directory in your project or the same directory as the file importing this code.
import pldato your code.
- See the demo below on how to use the actual model code.
- When you are all done,
you can deactivate the conda environment with
Demo with MNIST Handwritten Digits Data
- This demo shows you how to extract LDA features from your data.
- For classification, the model automatically preprocesses your data, but with the default preprocessing setting, it could overfit small training datasets.
- If you run into this issue, one way to address it is to reduce the number of principal components present in the preprocessed data.
- The MNIST demo shows you how simple this is: just supply an optional parameter.
If you created the Conda environment with the name
activate it with the following.
conda activate plda # If `plda` is the name you gave the Conda environment.
To run all tests (~120 seconds with ~60 CPU cores), use the following.
python3.5 pytest plda/ # This README.md should be inside here.
To run a particular test file, run one of the following.
pytest plda/tests/test_model/test_model_units.py # ~.66s for me. pytest plda/tests/test_model/test_model_integration.py # ~1.0s for me. pytest plda/tests/test_model/test_model_inference.py # ~80.6s for me. pytest plda/tests/test_optimizer/test_optimizer_units.py # ~.59s for me. pytest plda/tests/test_optimizer/test_optimizer_integration.py # ~.78s. pytest plda/tests/test_optimizer/test_optimizer_inference.py # ~25.3s for me. pytest plda/tests/test_classifier/test_classifier_integration.py # ~.69s.
Once you finish running the tests,
remove all the
__pycache__/ folders generated by pytest with the following.
py3clean plda/* # This README.md should be in here.
Finally, if you are done working with the model and test code, deactivate the Conda environment.
conda deactivate # You can run this from any directory.