I am using a CNN for sentiment analysis of news articles. It is a binary classification with outputs: Interesting & Uninteresting. In my dataset, there are around 50,000 Uninteresting articles and only about 200 Interesting articles. I know the ratio is badly skewed.
- My question is what should be the ratio in such a scenario.
- One approach that I want to try is to cluster the Uninteresting news articles and take a sample from each cluster for training. Is there a better approach?