CS 451 Quiz 14
Large scale machine learning; SVM cost function
What is a typical training set size for a modern "large dataset"? *
1 point
How can you tell that training with a large data set will give better performance than when training with just a small subset (m = 1000) of the data? *
1 point
Batch gradient descent means to make a single gradient descent steps after looking at *
1 point
For large training sets, stochastic gradient descent can be much faster than batch gradient descent *
1 point
In mini-batch gradient descent, a typical choice of the mini-batch-size b is *
1 point
In order to check stochastic gradient descent for convergence, we can compute the average of, say, the last 1000 cost values. For each training example, the cost value should be computed *
1 point
In order for stochastic gradient descent to converge, it can be a good idea to decrease the learning rate with the number of iterations. *
1 point
The cost function used in SVMs is similar to the cost function in logistic regression, but instead of using the log function *
1 point
In logistic regression, we have a parameter lambda controlling the amount of regularization. In SVMs, what do we have instead? *
1 point
SVM stands for *
1 point