Machine Learning Techniques, End Term
What is the role of the regularization term in ridge regression?
What is the role of the regularization term in ridge regression? Which of the following conditions must be satisfied for a decision tree to be pure at a given node? Consider that the three weight vectors $w_1, w_2$, and $w_3$ are learned for a four-dimensional dataset using a linear regression model or regularized linear regression model (Not in any particular order). $$w_1 = \begin{bmatrix} -0.41 & 0.26 & 0.54 & 0.17 \end{bmatrix}^T$$ $$w_2 = \begin{bmatrix} -0.81 & 0.89 & 0.93 & 0.52 \end{bmatrix}^T$$ $$w_3 = \begin{bmatrix} 0 & 0 & 0.08 & 0.2 \end{bmatrix}^T$$ Select the most appropriate match for these weight vectors.