Creating the Classification Model

Explore how to train and finalize a CatBoost classification model in PyCaret for NLP tasks. Learn to split data, train on full datasets, and save models for future use.

We'll cover the following...

Creating the model
Finalizing and saving the models
Implementation

Creating the model

The create_model() function lets us easily train a classification model on the dataset. In this case, we’ll create a CatBoost model because it generally performs well in classification tasks.

catboost = classification.create_model('catboost')

Run the code above in the Jupyter Notebook by ...

1.Introduction to Machine Learning

2.Regression

3.Classification

4.Clustering

Project

5.Anomaly Detection

6.Natural Language Processing

7.Deploying a Machine Learning Model

8.Conclusion

9.Appendix

Creating the Classification Model

Creating the model