Q. Which statement is true about neural network and linear regression models?

• (A) both techniques build models whose output is determined by a linear sum of weighted input attribute values
• (B) the only examples necessary to compute f(x) in an svm.
• (C) both models require numeric attributes to range between 0 and 1
• (D) both models require input attributes to be numeric