/Linear-Regression-Project-Weather-Prediction-

Linear Regression project with Ridge and Lasso Regression.

Primary LanguageJupyter Notebook

Linear-Regression-Project-Weather-Prediction-

Linear Regression project with Ridge and Lasso Regression.

Assignment Tasks:

 Import the training set "W05_train.txt“ and test set "W05_test.txt"

 The last column „relative_humidity_3pm“ is the target variable, the first 9 columns are input variables

 Fit a linear regression model to the training data using all input variables. Report the R2-score of the training and test set

 Fit a linear regression model to the training data using the first 6 input variables. Report the R2-score of the training and test set

 Fit a linear regression model to the training data using the first 7 input variables. Report the R2-score of the training and test set

 Fit a linear regression model to the training data using only the 7th input variable „relative_humidity_9am“. Report the R2-score of the training and test set

 Fit a ridge regression model to the training data using all input variables with alpha=10. Report the R2-score of the training and test set

 Fit a ridge regression model to the training data using all input variables with alpha=100. Report the R2-score of the training and test set as well as the value of the constant and all coefficients of the model

 Fit a lasso regression model to the training data using all input variables with alpha=10. Report the R2-score of the training and test set as well as the value of the constant and all coefficients of the model