How can you improve document classification accuracy?

How can you improve document classification accuracy?

In this article, I’ve illustrated the six best practices to enhance the performance and accuracy of a text classification model which I had used:

1. Domain Specific Features in the Corpus.
2. Use An Exhaustive Stopword List.
3. Noise Free Corpus.
4. Eliminating features with extremely low frequency.
5. Normalized Corpus.

Can you suggest some method for improving the accuracy of classifier model?

But, some methods to enhance a classification accuracy, talking generally, are: 1 – Cross Validation : Separe your train dataset in groups, always separe a group for prediction and change the groups in each execution. Then you will know what data is better to train a more accurate model.

How to improve classification accuracy for machine learning?

But, some methods to enhance a classification accuracy, talking generally, are: 1 – Cross Validation : Separe your train dataset in groups, always separe a group for prediction and change the groups in each execution. Then you will know what data is better to train a more accurate model.

How to improve the accuracy of text classification?

Improve your model my adding bigrams and tri-grams as features. Try doing some topic modelling like latent Dirichlet allocation or Probabilistic latent Semantic Analysis for the corpus using a specified number of topics – say 20. You would get a vector of 20 probabilities corresponding to the 20 topics for each document.

How to improve the accuracy of my supervised model?

Step one: Identify all of the settings in your model that might impact performance. These settings will either involve data transformation (such as min_df in tfidf) of model hyperparameters (such as max_features in your RandomForestClassifier). Step two: Wrap everything in a pipeline.

How to improve the accuracy of train classification?

There’s no way to help you properly without knowing the real problem you are treating. But, some methods to enhance a classification accuracy, talking generally, are: 1 – Cross Validation : Separe your train dataset in groups, always separe a group for prediction and change the groups in each execution.