A data scientist uses PROC HPNEURAL in SAS with TRAIN TECH=LEVMAR. What optimization algorithm does LEVMAR specify?
Select an answer to reveal the explanation.
Short Explanation
Here's the deal — you're looking at TECH=LEVMAR, so it specifies the Levenberg-Marquardt algorithm. It's a second-order method that blends gradient descent and Gauss-Newton, using a damping parameter to converge faster on small-to-medium networks.
Full Explanation
The correct choice is the Levenberg-Marquardt algorithm, a second-order optimization method that combines gradient descent and Gauss-Newton, because TECH=LEVMAR in PROC HPNEURAL specifies that training algorithm. It interpolates between steepest descent and the Gauss-Newton method and adapts its step size based on a damping parameter, converging faster than first-order methods for small-to-medium networks. Stochastic gradient descent with momentum is wrong because it would be specified with TECH=SGRADIENT. Adam optimizer with adaptive learning rates is wrong because it is available in SAS DLPy but not among PROC HPNEURAL's TECH= options. L-BFGS quasi-Newton method for large-scale neural network training is wrong because it would be specified with TECH=QUANEW in PROC HPNEURAL.