Welcome to the FAQ page for Infermatic.ai! Here, you can find answers to your questions about large language models and the AI industry. Whether you’re curious about how to use our tools or want to learn more about AI, this page is a great place to start.
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Related Questions
- How can we use metrics like Jaccard similarity and cosine similarity to compare topic models with human-defined categories?
- What are some techniques for evaluating the overlap between topics in a topic model and predefined categories, such as using V-measure or mutual information?
- Can we use clustering algorithms like k-means or hierarchical clustering to group topics from a topic model with human-defined categories and measure the similarity between them?
- How can we use semantic role labeling or named entity recognition to improve the alignment between topics in a topic model and human-defined categories?
- What is the role of human evaluation in assessing the overlap between topics in a topic model and human-defined categories?
- Can we use topic coherence measures like Perplexity or Normalized Pointwise Mutual Information to evaluate the similarity between topics in a topic model and human-defined categories?
- How can we use active learning or semi-supervised learning to improve the alignment between topics in a topic model and human-defined categories?
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