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https://github.com/s1998/dsc291-linearalgebra


https://github.com/s1998/dsc291-linearalgebra

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# dsc291-linearAlgebra

To run the baselines related to linear algebra, use the notebook `matrixfactorization_notebook.ipynb`
The notebook has been properly commented and divided into sections for explaining everything.

To run the transformers based models, use the file `transformersTrain.py`.
It runs the code on the given datasets. The file has been commented to provide appropriate pointers.
Also, the logs for the same are present oin twitterCovidKaggleLogs.

Experiemtal results obtained :

| Method name | Micro-F1 | Macro-F1 | Weighted-F1 |
|:--------------:|:--------:|:--------:|:-----------:|
| Sparse Vectors | 0.547 | 0.557 | 0.547 |
| LSA | 0.376 | 0.369 | 0.369 |
| NNMF | 0.350 | 0.334 | 0.339 |
| BERT | 0.858 | 0.853 | 0.858 |

Environment assumes the following:

sentence-transformers==1.2.0

transformers==3.5.1

scikit-image==0.17.2

scikit-learn==0.23.2

numpy==1.19.5

pandas==1.1.5