Philgoo Han writeup of Klein and Manning
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Jump to navigationJump to searchThis is a review of Klein_2002_conditional_structure_versus_conditional_estimation_in_nlp_models by user:Ironfoot.
- Where is the perfomance comming from, the structure, objective function or the feature selection.
- Different objective functions (loss function)
- Joint likelihood
- Conditional likelihood: This must be something like logistic regression?
- Sum of conditional likelihood
- Any other important objectives?
- Scoring
- Accurcacy : Why use this specific scoring?
- Optimization
- What is a deficient model? Probability may not sum up to 1?
- How do you know a certain local optima is global in actual?
- Result
- CL is generally better than JL
- Any tunning possible for rare observations in JL?
- Can we make a criterion depending on the data(feature) without actually testing both?
- CL is generally better than JL
- Different model structure
- HMM
- Objective function: JL, CL
- CMM
- Observation bias
- Label bias is not much likely to occur
- HMM
