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Challenge | Multivariate Linear Regression
Explore the Linear Regression Using Python
course content

Contenido del Curso

Explore the Linear Regression Using Python

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

Tarea

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

Your plan:

  1. [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.
  2. [Line #25-26] Initialize and fit the model (assign the model to the variable model2).
  3. [Line #30-31] Calculate the MAE and assign the result to the variable MAE.
  4. [Line #34-35] Calculate the R-squared and assign the result to the variable r_squared.
  5. [Line #38] Print the intercept, the MAE and the R-squared in this order and round each value to second digit.

Tarea

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

Your plan:

  1. [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.
  2. [Line #25-26] Initialize and fit the model (assign the model to the variable model2).
  3. [Line #30-31] Calculate the MAE and assign the result to the variable MAE.
  4. [Line #34-35] Calculate the R-squared and assign the result to the variable r_squared.
  5. [Line #38] Print the intercept, the MAE and the R-squared in this order and round each value to second digit.

Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones

¿Todo estuvo claro?

Sección 5. Capítulo 3
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Challenge

Tarea

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

Your plan:

  1. [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.
  2. [Line #25-26] Initialize and fit the model (assign the model to the variable model2).
  3. [Line #30-31] Calculate the MAE and assign the result to the variable MAE.
  4. [Line #34-35] Calculate the R-squared and assign the result to the variable r_squared.
  5. [Line #38] Print the intercept, the MAE and the R-squared in this order and round each value to second digit.

Tarea

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

Your plan:

  1. [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.
  2. [Line #25-26] Initialize and fit the model (assign the model to the variable model2).
  3. [Line #30-31] Calculate the MAE and assign the result to the variable MAE.
  4. [Line #34-35] Calculate the R-squared and assign the result to the variable r_squared.
  5. [Line #38] Print the intercept, the MAE and the R-squared in this order and round each value to second digit.

Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones

¿Todo estuvo claro?

Sección 5. Capítulo 3
toggle bottom row

Challenge

Tarea

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

Your plan:

  1. [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.
  2. [Line #25-26] Initialize and fit the model (assign the model to the variable model2).
  3. [Line #30-31] Calculate the MAE and assign the result to the variable MAE.
  4. [Line #34-35] Calculate the R-squared and assign the result to the variable r_squared.
  5. [Line #38] Print the intercept, the MAE and the R-squared in this order and round each value to second digit.

Tarea

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

Your plan:

  1. [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.
  2. [Line #25-26] Initialize and fit the model (assign the model to the variable model2).
  3. [Line #30-31] Calculate the MAE and assign the result to the variable MAE.
  4. [Line #34-35] Calculate the R-squared and assign the result to the variable r_squared.
  5. [Line #38] Print the intercept, the MAE and the R-squared in this order and round each value to second digit.

Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones

¿Todo estuvo claro?

Tarea

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

Your plan:

  1. [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.
  2. [Line #25-26] Initialize and fit the model (assign the model to the variable model2).
  3. [Line #30-31] Calculate the MAE and assign the result to the variable MAE.
  4. [Line #34-35] Calculate the R-squared and assign the result to the variable r_squared.
  5. [Line #38] Print the intercept, the MAE and the R-squared in this order and round each value to second digit.

Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
Sección 5. Capítulo 3
Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
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