A data scientist runs PROC HPNEURAL for regression. Which option correctly specifies that the output layer should use a linear (identity) activation function for a continuous target?
Select an answer to reveal the explanation.
Short Explanation
Here's the deal — PROC HPNEURAL automatically picks the output activation from the target type. For a continuous regression target, it uses linear identity activation, so you don't need to specify the output activation yourself.
Full Explanation
The correct choice is that PROC HPNEURAL automatically uses linear activation for regression targets, with no specification needed. PROC HPNEURAL selects output activation from the target type: linear identity for continuous targets and logistic for binary targets. The output-layer softmax option is wrong because softmax is not the linear identity activation used for a continuous regression target. The hidden-layer linear option is wrong because it uses the hidden statement for the output layer rather than specifying the output layer. The output-layer logistic option is wrong because logistic activation suits binary targets, not continuous regression.