wiki:ai:llm_regression
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| wiki:ai:llm_regression [2025/05/14 18:56] – created jmiller | wiki:ai:llm_regression [2025/05/15 13:30] (current) – jmiller | ||
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| Feature selection and preparation (choosing which features to include in the model, and calculations applied to them to help ensure a better fit). Algorithm selection (We explored linear regression in the previous example, but there are many other regression algorithms) Algorithm parameters (numeric settings to control algorithm behavior, more accurately called hyperparameters to differentiate them from the x and y parameters). After multiple iterations, the model that results in the best evaluation metric that's acceptable for the specific scenario is selected. | Feature selection and preparation (choosing which features to include in the model, and calculations applied to them to help ensure a better fit). Algorithm selection (We explored linear regression in the previous example, but there are many other regression algorithms) Algorithm parameters (numeric settings to control algorithm behavior, more accurately called hyperparameters to differentiate them from the x and y parameters). After multiple iterations, the model that results in the best evaluation metric that's acceptable for the specific scenario is selected. | ||
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wiki/ai/llm_regression.1747248961.txt.gz · Last modified: by jmiller
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