1. Explain linear regression in detail.
2. Explain train test split approach and K-folds cross validation techniques.
3. Explain ridge regression in detail.
4. Explain lasso regression in detail.
5. Define root node, leaf node and intermediate node of decision trees.
6. Define splitting and pruning of trees.
7. Construct a decision tree for the following dataset.

Predictors Target Outlook Temp Humidity Windy Hours Played Outlook Rainy Hot High Falce 26 Rainy Hot High True 30 Overact Hot High Falce 48 Sunny Mild High Falce 46 Sunny Rainy Overcast Sunny Cool Normal Falce 62 Sunny Cool Normal True 23 Overact Cool Normal True 43 Windy 46.3 Temp. Rainy Mild High Falce 36 Rainy Cool Normal Falce 38 Sunny Mild Normal Falce 48 FALSE TRUE Cool Hot Mild Rainy Mild Normal True 48 Overcast Mild High True 62 47.7 26.5 38 27.5 41.5 Overcast Hot Normal Falce 44 Sunny Mild High True 30