Modeling Notebook#3
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…tebook This should be as an initial base which we could iterate and improve the data preparation for the model. This notebook includes the following: - Split dataset into training and test datasets by sklearn library - Extracting features from columns such as embedding, word count, etc - Feature selection, which drops comment text, and unnecesary columns - Sklearn pipelines, column transformer Acked-by: Atlls <alejandroaigner1999@hotmail.com> Signed-off-by: A.L.I.C.E <a@alice0.com>
The phase 3 contains two elements which are:
- final feature matrices: this outputs the transformed dataset from
original data in `data/` directory, along the needed columns
to operate with.
- artifacts persistence: this dumps the column transformer into
preprocess_pipeline.joblib, and asso dumps a tuple stored as
(X_train_final, X_test_final, Y_train, Y_test) into
split_data.joblib.
- output summary: a summary about data processing notebook outputs,
and some design choices..
Signed-off-by: A.L.I.C.E <a@alice0.com>
Signed-off-by: A.L.I.C.E <a@alice0.com>
Signed-off-by: A.L.I.C.E <a@alice0.com>
Signed-off-by: A.L.I.C.E <a@alice0.com>
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Nota, optuna n_trials establecido a 2, verificar con 30.
Nada agregado de diferente respecto a #1 y #2 , solo verificar
notebook/modeling_and_model_selection.ipynb.