Ai Chapter 4 (2122-1) Quiz 3

Machine learning concerns the contruction and study of systems that can learn from ____.

• data

• designer experience

• mistake

• algorithm

A, B and C in the image are ___, ___, and ___.

• Object recognition, Statistical learning, and Computer Vision

• Statistical learning, Computer vision, and kindergarten learning

• Computer vision, Machine vision, Wanda vision

• Object recognition, Object orientation, Computer vision

1 & 2 in the image are ____ and ____.

• Reinforcement learning and Unsupervised learning

• Deep purple and Reinforcement learning

• Deep meaning and Semi-unsupervised learning

• Reinforcement learning and Deep calculation

The person who says "Machine learning is about predicting the future" is ____.

• Hal Daume III

• Ethe Alpaydin

• Kevin P. Murphy

• Christopher M. Bishop

The success of a machine learning system depends on the algorithm. The algorithms control the search to find and build the _______.

• knowledge structures

• knowledge databases

• database structures

• information structures

Which one is the best for explaining semi-supervised learning?

• Training data includes a few desired outputs

• Training data does not include desired outputs

• Training data includes desired output

• Rewards from a sequence of actions

Generalization beyond the training data is delayed until a new instance is provided to the system. This statement refers to ______________.

• Instance-based learning

• Hebb learning rule

• gradient descent learning algorithm

• decision tree

Underfitting: ___________.

• When the model is too simple, both training and test errors are large

• This means that it learns the training set too well

• This means that it learns the training set moderately

• When learning time takes too long

Density estimation falls under ___________learning category.

• unsupervised

• supervised

• semi-supervised

• reinforcement

Reinforcement learning goal is to find a suitable action model that would maximize the ______________of the agent.

• total cumulative rewards

• total cumulative commissions

• average cumulative rewards

• total cumulative tokens