canonical form to standard form

which extends k- - Nearest Neighbors by learning to compress your training dataset * :down in size Support vector machines O Classification and regression trees O Learning Vector Quantization O k-Nearest NeighborsPlease convert from canonical form to standard form! Canonical Form to Standard Form 2. Convert the following expression from standard form (3 variables) to canonical form (sum-of-minterms) : F = (ab' + c')c + (b + c)'Part one - evalboostforest( ) _ 1. Import alpha and trained model 2. Derive prediction using alphalil * treelil.predict(xTe) Part two - GBRT( ) function when i = 1 1. Import Regression Tree model 2. Train Regression Tree with xTr and yTr training data 3. Append trained model and alpha o trees = tree(xTryTr) 4. Derive the prediction (PredHi) using evalboostforest0 function predHi = alpha' tree(xTr. yTr) when i = 2 1. Import Regression Tree model 2. Train Regression Tree with xTr and residual(yTr - PredHi) training data 3. Append trained model and alpha o trees = tree(xTr. yTr) + tree(xTr, yTr - PredH1) 4. Derive the prediction (PredH2) using evalboostforest() function predH2 = alpha' tree(xTr, yTr) + alpha ' tree(xTr. yTr - PredH1) when i = 3 1. Import Regression Tree model 2. Train Regression Tree with xTr and residual(yTr - PredHi) training data 3. Append trained model and alpha trees = tree(xTr. yTr) + tree(xTr, yTr - PredH1) + tree(xTr, yTr - PredH2) 4. Derive the prediction (PredH2) using evalboostforest() function predH3 = alpha ' tree(xTr. yTr) + alpha' tree(xTr, yTr - PredHi) + alpha' tree(xTryTr - PredH2)Question 1 1 pts Which type of modeling focuses on accurate predictions only? 0 Predictive modeling 0 Explanatory modeling Q Descriptive analytics 0 Multiple linear regression Question 2 1 pts A decision tree to predict the salary of an employee is called a 0 Regression Tree 0 Classication Tree 0 tree diagram 0 Categorical Variable Tree