How can you improve document classification accuracy?
Table of Contents
How can you improve document classification accuracy?
Improving accuracy of Text Classification
- Broke the documents in list of words.
- Removed stop words, punctuations.
- Performed stemming.
- Replaced numerical values with ‘#num#’ to reduce vocabulary size.
- Transformed the documents into TF-IDF vectors.
How can you improve the classification of an image?
Add More Layers: If you have a complex dataset, you should utilize the power of deep neural networks and smash on some more layers to your architecture. These additional layers will allow your network to learn a more complex classification function that may improve your classification performance. Add more layers!
How do you improve classification accuracy deep learning?
Here is the checklist to improve performance:
- Analyze errors (bad predictions) in the validation dataset.
- Monitor the activations.
- Monitor the percentage of dead nodes.
- Apply gradient clipping (in particular NLP) to control exploding gradients.
- Shuffle dataset (manually or programmatically).
How do I increase my fastText accuracy?
For getting higher accuracy, fastText uses some other tricks: filtering rare words, considering letter n- grams (sub-words) [2], word n-grams, etc. These tricks improve the classification accuracy, but their effects are not critical for formal analysis of fastText classification model.
How can you improve accuracy of image classification models?
Get More Data One of the easiest ways to increase validation accuracy is to add more data. This is especially useful if you don’t have many training instances. If you’re working on image recognition models, you may consider increasing the diversity of your available dataset by employing data augmentation.
How do I improve my photo classification on CNN?
To improve CNN model performance, we can tune parameters like epochs, learning rate etc.. Number of epochs definitely affect the performance. For large number of epochs , there is improvement in performance….
- Train with more data: Train with more data helps to increase accuracy of mode.
- Early stopping:
- Cross validation:
How can I improve my MLP performance?
Now we’ll check out the proven way to improve the performance(Speed and Accuracy both) of neural network models:
- Increase hidden Layers.
- Change Activation function.
- Change Activation function in Output layer.
- Increase number of neurons.
- Weight initialization.
- More data.
- Normalizing/Scaling data.