👉 Estimability is a concept in computational linguistics, specifically in natural language processing (NLP) and machine learning. In this context, it refers to the property of a model or algorithm that allows for its predictions to be highly accurate even when the underlying data is noisy or incomplete. In NLP, estimableness refers to models that can produce outputs with high accuracy under certain conditions, such as when the training data is well-sampled or the model has been trained on a large dataset.
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What is the definition of Estimable? 🙋
👉 In the field of statistics and probability, "estimable" refers to something that is relatively reliable or accurate. It implies that a result or prediction is likely to be as precise or close as possible to what it represents, without being too far off from it. For example, in a study on weather patterns, if the average temperature for a particular region is estimated to be 30°C with a margin of error of ±2°C, this means that the actual temperature will vary within about
