Feature Generation and Selection in Pattern Recognition Systems

Meaning that we want to find a new representation in terms of ______.

This stage concerns the ______ generation stage of the design of a classification system that performs a given pattern recognition task.

This is also a very important task, and it concerns the ______ selection stage of the classification system.

In the preceding classification example, the straight line was drawn ______, just to please the eye.

Problems for which a linear classifier (straight line or hyperplane in the ______-dimensional space) can result in acceptable performance are not the rule.

What type of ______ must one adopt, and what type of optimizing criterion must be used in order to locate a surface in the right place in the l-dimensional feature space?

In ______ Pattern Recognition, the model learns without direct guidance.

______ is the assignment of a class name to a pattern by evaluating a trained classifier for that pattern.

______ and Sensing gathers the observations to be classified or described.

A ______ is a procedure that distinguishes the classes of interest.

Pre-Processing involves ______ of noise in data.

______ involves isolating patterns of interest from the background.

_______ is a good tool to deal with noisy data and uncertainty in practical problems.

Formal language theory provides the background for ______ pattern recognition.

An artificial neural network is modeled after the neural network in the ______.

Neural Network Approach is the most popular technique for detecting patterns today due to its ability to recognize patterns in different types of data, whether ______, visual, or auditory.

Machine learning can be summarized as learning a function that maps input variables (X) to output variables (Y). Y = f(X) An algorithm learns this target mapping function from ______ data.

Our job as machine learning practitioners is to evaluate different machine learning algorithms and see which is better at approximating the underlying ______.