Answers
Solution:
Select all reasonable methods for handling local minima when training an ANN (Artificial Neural Networks):
a. restart the training several times from the same initial state
b. use simulated annealing
c. perturb the weight matrix slightly and continue the training
Select all that are true in regard to the hidden units of a fully-connected ANN:
a. unlike decision tree nodes, ANN nodes have a meaning that can be clearly interpreted
d.
There must be the same number of units in each hidden layer in the network
Select the reasons that the computational complexity of the convolutional NN (CNN) allows researchers to create a 313 layer network to train on ImageNet (millions of images) within a reasonable time.
a. Images are down sampled to a much smaller size.
b. For one layer, a single k x k convolutional weight matrix (also know as a kernel) is learned, rather than separate matrices for each k x k grid in the image.
c. The pooling layers generally down sample the features, for example, by replacing a 2x2 grid with its max value.
On which of the following data is it possible to use CNNs?
e. Sequence-based data
Select all of the disadvantages to performing evaluation by using k-fold CV versus using separate training and test datasets?
a.
When you tune hyper-parameters, you are tuning effectively them to the test set; so you will overestimate performance (such as accuracy) that you expect on unseen/production data.
c. The effective size of your test set is much smaller in k-fold CV.