Interested to Buy Any Domain ? << Click Here >> for more details...
What are the steps to build and evaluate a linear regression model in r?
- 1 Answers
- 103 Views
- I also Faced
- E-Mail Answers
Answer / Nalini Johari
To build and evaluate a linear regression model in R, follow these steps: n1. Load your data into R. n2. Check for missing values and remove them if necessary. n3. Preprocess the data as needed (e.g., convert factors to numeric). n4. Split the data into training and testing sets. n5. Fit a linear regression model using the `lm()` function: `linear_model <- lm(dependent_variable ~ independent_variables, data = training_data)`. n6. Evaluate the performance of the model on the test set using appropriate metrics (e.g., R-squared, mean squared error).
| Is This Answer Correct ? | 0 Yes | 0 No |
how would you build a scatter-plot using plotly?
What is a random forest? How do you build and evaluate a random forest in r?
Explain how to read data or a matrix from a file?
What is function in r?
How would you do a cross-product of two tables in r?
What is a white noise model and how can you simulate it using r?
What makes a valid variable name in R?
What is transpose?
What are R Functions?
Explain r graphics devices?
What is the function used for adding datasets in R?
Name some functions which can be used for debugging in r?
C 
