Which of the following statements about various neural network layers is true? (Multiple Answers Possible)   A. A perceptron, or fully-connected layer, lacks the ability to capture class imbalance information in training data.   B. A multi-layer perceptron can consider the interactions between multiple input fea- tures and an output class.   C. A convolutional layer is best applied when the input to that layer contains local structure.   D. A pooling layer can only be applied to 2-dimensional or higher input data.   E. A vanilla RNN cell can be formulated as a fully-connected layer operation, half of whose inputs at each timestep from previous output and half from an input sequence.

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
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Which of the following statements about various neural network layers is true? (Multiple Answers Possible)

 

A. A perceptron, or fully-connected layer, lacks the ability to capture class imbalance information in training data.

 

B. A multi-layer perceptron can consider the interactions between multiple input fea- tures and an output class.

 

C. A convolutional layer is best applied when the input to that layer contains local structure.

 

D. A pooling layer can only be applied to 2-dimensional or higher input data.

 

E. A vanilla RNN cell can be formulated as a fully-connected layer operation, half of whose inputs at each timestep from previous output and half from an input sequence.

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