Objective:
Use topic model to map and label transaction data into various categories.
Our dataset contain 176 rows and for we to get a better mapping or topic, we need a corpus more than what we have.
So, therefore, we will use just three categories for this project and as we get more dataset, we will product more topics.
Selected topics:
- Online transactions
- Charges
- Others
Steps:
- Data cleaning
- data preprocessing
- BERT Topic mode
- Guided Bert Topic Model
- Guided LDA model
- Evaluation
- Save model
- Topic mapping for auto labelling
- Vectorization for Baseline Classifier
- Baseline Classifier training and export model
- Baseline model sample prediciton