Here is a simple competitive learning algorithm to find three clusters within some input data.

Boosting is a general method for improving the accuracy of any given learning algorithm.

Needless to say, there are better learning algorithms for weights of patterns.

With this problem, however, the supervised learning algorithm will only have five labeled points to use as a basis for building a predictive model.

A stable learning algorithm would produce a similar classifier with both the 1000-element and 999-element training sets.

Determine the structure of the learned function and corresponding learning algorithm.

A wide range of supervised learning algorithms is available, each with its strengths and weaknesses.

Tuning the performance of a learning algorithm can be very time-consuming.

When is large, the learning algorithm will have high bias and low variance.

It has several significant advantages over more traditional neural net learning algorithms.