课程: Complete Guide to AI and Data Science for SQL: From Beginner to Advanced
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Creating the linear regression model and model summary: Part 2 - SQL教程
课程: Complete Guide to AI and Data Science for SQL: From Beginner to Advanced
Creating the linear regression model and model summary: Part 2
- [Instructor] Okay, before we move on, here is a good spot to pause the video and take a breather. There are a lot of numbers to take in, so don't be afraid to rewind and review what has been discussed thus far before we move on. Okay, now let's talk about the coefficients. Think of them as the key players in your model. Among them, we have const, which represents the intercept or starting point of our predictions. Similar to where a journey begins on a map, it's like the initial reference point for making predictions. It tells you where your predictions begin on the scale. Now, each predictor variable, like crime rate or river boundary, gets a coefficient. Think of the predictor variables such as crime rate or river boundary as key players in your model. Each one has its own coefficient, which is like a scorecard telling you both the direction, up or down, and the strength of their influence on home value log. It's…
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Creating the linear regression model and model summary: Part 19 分钟 33 秒
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Creating the linear regression model and model summary: Part 27 分钟 16 秒
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Creating the linear regression model and model summary: Part 35 分钟 33 秒
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Dropping insignificant variables and re-creating the model7 分钟 57 秒
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Checking assumptions for linear regression3 分钟 18 秒
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Assumption 1: Checking for mean residuals2 分钟 47 秒
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Assumption 2: Checking homoscedasticity3 分钟 13 秒
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Assumption 3: Checking linearity2 分钟 12 秒
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Assumption 4: Checking normality of error terms3 分钟 24 秒
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Q-Q plot for checking the normality of error terms3 分钟 14 秒
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Model performance comparison on train and test data6 分钟 7 秒
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Applying cross-validation and evaluation4 分钟 40 秒
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Challenge: Model building48 秒
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Solution: Model building1 分钟 16 秒
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