Describe various aspects of machine learning training for regression training such as cost function, Gradient Descent, and Bias-Variance Tradeoff.

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Learning Goal: I’m working on a machine learning writing question and need an explanation and answer to help me learn.Optimization of regression models:Describe various aspects of machine learning training for regression training such as cost function, Gradient Descent, and Bias-Variance Tradeoff. The initial post must be between 250-300 words in length.Nutrition Case Study:The main objective is to write a fully executed R-Markdown program performing regression prediction for the response variable using the best models found for kNN, Random Forest and XGBoost techniques predicting the response variable in the Nutrition case study. Make sure to describe the final hyperparameter settings of all algorithms that were used for comparison purposes.You are required to clearly display and explain the models that were run for this task and their effect on the reduction of the Cost Function.Points will be deducted in case you fail to explain the output. Please share the answers in 2 separate documents.
Requirements: 300 words/depends

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