Explabox demo for the UCI drug reviews dataset
Project description
explabox-demo-drugreview
Welcome to the demo of the explabox on the UCI Drug Reviews dataset. To speed up the demo, we made a smaller subset of the train and test dataset. The demo
also includes a pretrained black-box classifier, which aims to predict whether a review
in the text got a rating
of
negative
(1-5), neutral
(5-6) or positive
(6-10).
To start the demo, you require:
- Python 3.8 or above (see the installation guide)
- Jupyter Notebook installed (see the installation guide)
Install the demo via:
pip3 install explabox
pip3 install explabox-demo-drugreview
Importing the necessary files
To start the demo, open your Jupyter Notebook and run the following line:
from explabox_demo_drugreview import model, dataset_file
The dataset_file
is the location of the dataset (drugsCom.zip
), containing a train split (drugsComTrain.tsv
) and test split (drugsComTest.tsv
). You can import this dataset with the explabox with the data in the column review
and labels in the column rating
:
from explabox import import_data
data = import_data(dataset_file, data_cols='review', label_cols='rating')
The model can directly be imported as-is. Make sure you explicitly include that drugsComTrain.tsv
includes the train
split and drugsComTest.tsv
the test
split of the data:
from explabox import Explabox
box = Explabox(data=data,
model=model,
splits={'train': 'drugsComTrain.tsv', 'test': 'drugsComTest.tsv'})
Now you are ready to .explore
, .examine
, .expose
and .explain
with the explabox!
Documentation
Having trouble? Want to know which functionalities the explabox includes? Check out the documentation at https://explabox.rtfd.io.
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