Course Content

Explore the Linear Regression Using Python

1. What is the Linear Regression?

2. Correlation

3. Building and Training Model

4. Metrics to Evaluate the Model

5. Multivariate Linear Regression

Challenge

Task

Swipe to start coding

Let’s indicate the number of nonflavanoid phenols based on the number of flavanoids, total phenols and evaluate our model.

Your plan:

[Line #24] Split the data 70-30 (70% of the data is for training and 30% is for testing) and insert 1 as a random parameter.
[Line #25-26] Initialize and fit the model (assign the model to the variable model2).
[Line #30-31] Calculate the MAE and assign the result to the variable MAE.
[Line #34-35] Calculate the R-squared and assign the result to the variable r_squared.
[Line #38] Print the intercept, the MAE and the R-squared in this order and round each value to second digit.

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Everything was clear?

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Section 5. Chapter 3

Task

Swipe to start coding

Let’s indicate the number of nonflavanoid phenols based on the number of flavanoids, total phenols and evaluate our model.

Your plan:

[Line #24] Split the data 70-30 (70% of the data is for training and 30% is for testing) and insert 1 as a random parameter.
[Line #25-26] Initialize and fit the model (assign the model to the variable model2).
[Line #30-31] Calculate the MAE and assign the result to the variable MAE.
[Line #34-35] Calculate the R-squared and assign the result to the variable r_squared.
[Line #38] Print the intercept, the MAE and the R-squared in this order and round each value to second digit.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your feedback!

Section 5. Chapter 3

Switch to desktop for real-world practiceContinue from where you are using one of the options below