Exam 5: Machine-Learning Techniques for Predictive Analytics

The use of hidden layers and new topologies and algorithms renewed waning interest in neural networks.

In supervised learning techniques, such as backpropagation, the training data consist of vector pairs-an input vector and a target vector.

Model ensembles tend to be more robust against outliers and noise in the data set than individual models.

Describe the Tree Augmented Naïve (TAN) Bayes method.

Why have neural networks shown much promise in many forecasting and business classification applications?

Which of the following are advantages of the Naïve Bayes method or classification?

Because of their complexity, it is more difficult to understand the inner structure of model ensembles (how they do what they do) than individual models.

List the pros and cons of model ensembles compared to individual models.

Describe the taxonomy for model ensembles.

How is a general Hopfield network represented architecturally?