Given the code to add a concatenation layer:

Assume the output dimensions (width*depth):

source layer A 100*100*5 source layer B 100*100*5 source layer C 100*100*3

What is the correct dimension of the output of this concatenation layer?

A. 100'100'13

B. 300'300'5

C. 100'100'18

D. 300'300'13

Which statements are TRUE about importing SAS Contextual Analysis projects into SAS Visual Text Analytics when creating a new project? (Choose two)

A. All custom concept and some predefined concept settings are imported

B. All machine generated topics and sentiment scores are imported

C. All custom categories are imported

D. All sentiment classification and probability scores are imported

Which statement describes a situation in which a bi-directional recurrent neural network is a better option than a unidirectional network?

A. The data at any given point in time depends on both the previous and subsequent elements of the sequence

B. The data at any given point in time depends only on the previous elements of the sequence

C. The data at any given point in time is independent of both the previous and subsequent elements of the sequence

D. The data at any given point in time depends only on the subsequent elements of the sequence

Which statement is TRUE about the QN modifier as it is used in the LITI language?

A. The @N modifier is a NOT (negation) modifier

B. The @N modifier is available in all concept rules

C. The @N modifier expands a noun term to include all noun stemmed variants of the term

D. The @N modifier specifies the starting byte location N where a word should be found

Given an equivalent number of neurons why would you use an LSTM-based recurrent neural network over a conventional recurrent neural network?

A. Implementation advantages - easier lo parallelize

B. Size - uses (ewer parameters

C. Efficiency-requires fewer computations

D. Sequence memory - learns data dependencies spanning more sequence elements