Closed kbogas closed 3 years ago
I checked it and it ran as expected.
My only comment is: shouldn't we return a list of all extracted features in from extract_features(), e.g. as a dict of filenames-->featurevectors. Otherwise, currently one would need to load the csvs (output/lda_features.csv, output/nmf_features.csv, output/tfidf_features.csv).
Works fine for me too.
This is in response to #3 .
Added first working version for the textual component.
Models implemented:
Added a simple evaluation process (printing the most similar pair of movies found) and streamlined the code to be modular for new models.
The whole module works using a very basic settings.yaml containing all the info about data paths, which models will be used, hyperparams etc.
For the time being, I made the assumption that we persist both the features and the models (if needed) to a local folder.
This means that the generated features for each model are saved in a .csv file in the output folder, alongside the corresponding pickled model if needed.
@tyiannak We will need to discuss a formal way of operating across the module regarding features, persistency, evaluation, testing etc?