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Model Diagnostics and Assumption Testing

Model Diagnostics and Assumption Testing - SQL教程

课程: Complete Guide to AI and Data Science for SQL: From Beginner to Advanced

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Model Diagnostics and Assumption Testing

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- [Instructor] Welcome back to your journey through the world of machine learning and regression analysis. After exploring the construction and application of regression models, let's pivot to a crucial phase, ensuring the integrity and reliability of your models through diagnostic and assumption testing. Imagine your skate park is bustling with skaters, each maneuvering the ramps with their unique style. Just as a skate inspector assesses the part's safety and design, model diagnostics allow you to evaluate your regression model's health, ensuring it accurately captures the essence of your data story. Earlier, you touched on the foundational assumptions of regression analysis as you explored the relationship between skate park design, or predictor variables, and skater performance or outcome variable. These assumptions include: linearity, independence, homoscedasticity, and your normality of residuals, which are vital for your model's accuracy and predictive power. Let's break these…

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