Statistical Estimators I: Overview
Goal: To derive a good probability estimate for the target feature based on observed data
Running Example: From n-gram data P(w1,..,wn)’s predict P(wn|w1,..,wn-1)
Solutions we will look at:
- Maximum Likelihood Estimation
- Laplace’s, Lidstone’s and Jeffreys-Perks’ Laws
- Held Out Estimation
- Cross-Validation
- Good-Turing Estimation