Classify Kaggle Consumer Finance Complaints into 11 classes. Build the model with CNN (Convolutional Neural Network) and Word Embeddings on Tensorflow.
Hello,
I am able to successfully run the small-sample.json file to get the prediction.json. The small-sample.json file is having information on "product" and "consumer_complaint_narrative". For the test file, this is fine. However, I am little confused (as I am new to this...) on the input file format of some unseen data (e.g., consumer_complaint_narrative ). My problem is how to get the "new prediction" of "consumer_complaint_narrative" without providing the "product:" field in the input.json file.
How does the input file format look like for just unseen "consumer_complaint_narrative" data and what should be prediction command? Do I need to edit anything in predict.py?
Can anyone help?
Thanks in advance.
Hello, I am able to successfully run the small-sample.json file to get the prediction.json. The small-sample.json file is having information on "product" and "consumer_complaint_narrative". For the test file, this is fine. However, I am little confused (as I am new to this...) on the input file format of some unseen data (e.g., consumer_complaint_narrative ). My problem is how to get the "new prediction" of "consumer_complaint_narrative" without providing the "product:" field in the input.json file. How does the input file format look like for just unseen "consumer_complaint_narrative" data and what should be prediction command? Do I need to edit anything in predict.py? Can anyone help? Thanks in advance.