explabox-demo-drugreview 0.9b12

Explabox demo for the UCI drug reviews dataset

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.