灰色深瞳
or the following questions please give a True or False answer。
1.1 A linear regression model will be developed using a training data set. Adding variables to the model will always reduce the sum of squared residuals measured on the validation set.
false
1.2 Although forward selection and backward elimination are fast methods for subset selection in linear regression, only step-wise selection is guaranteed to find the best subset.
1.3 An analyst computes classification functions using discriminant analysis for a data set with three classes C1, C2 and C3. She assumes that all three classes are equally likely to arise in the application. She later learns that the probability of C1 is twice that of C2 and C3. The probabilities for C2 and C3 are equal. If she re-computes the classification functions using this information, the value of the classification function for C1 will increase for every data point.
1.4 A classification model's misclassification rate on the validation set is a better measure of the model's predictive ability on new data than its misclassification rate on the training set.
1.5 A neural net classifier for two classes constructs a separating boundary between the classes
that is linear in weighted sums of the input values.