Please answer the 2 questions below. These questions are in regards to data mining.

Assume we have two models: Model M1: accuracy=85%. tested on 30 instances Model M2: accuracy=75%. tested on 5000 instances Which of the following statement is true? M1 is always more accurate than M2. M1 is always less accurate than M2. M1 is sometimes less accurate than M2. None of the above. Which of the following statements is true? Bagging improves accuracy by taking the sign of the sum of predicted values of each round. Same data item will only appear once in a round in bagging. Different weight is assigned to each data item in bagging. In bagging, if we have 100 samples, then we will do 99 rounds