Raw LLM Responses

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Comment
You are correct, that is the formula for Variance used in statistics. In Machine Learning, we replace the first term, f(x), with the "known outcomes", and the second term, E(f(x)), with the outcomes predicted by the model. As a result, we get what I described in this video. For more details, see page 34 of the Introduction to Machine Learning. Here is the relevant passage: "What do we mean by the variance and bias of a statistical learning method? Variance refers to the amount by which f(x) would change if we estimated it using a different training data set."
youtube AI Bias 2020-11-11T17:0…
Coding Result
DimensionValue
Responsibilitynone
Reasoningunclear
Policynone
Emotionindifference
Coded at2026-04-27T06:26:44.938723
Raw LLM Response
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