J. Zhang 's New Advances in Machine Learning PDF

J. Zhang 's New Advances in Machine Learning PDF

By J. Zhang

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2 Advantages and Disadvantages of SOM Self organise map has the following advantages: • • Probably the best thing about SOMs that they are very easy to understand. It’s very simple, if they are close together and there is grey connecting them, then they are similar. If there is a black ravine between them, then they are different. Unlike Multidimensional Scaling or N-land, people can quickly pick up on how to use them in an effective manner. Another great thing is that they work very well. As I have shown you they classify data well and then are easily evaluate for their own quality so you can actually calculated how good a map is and how strong the similarities between objects are.

The number of input and output units is defined by the problem (there may be some uncertainty about precisely which inputs to use, a point to which we will return later. However, for the moment we will assume that the input variables are 32 New Advances in Machine Learning • intuitively selected and are all meaningful). The number of hidden units to use is far from clear. As good a starting point as any is to use one hidden layer, with the number of units equal to half the sum of the number of input and output units.

Hodge, V. A. (2004). A Survey of Outlier Detection Methodologies. Artificial Intelligence Review , 22 (2), 85-126. Holland, J. (1980). Adaptive Algorithms for Discovering and Using General Patterns in Growing Knowledge Bases Policy Analysis and Information Systems. 4 (3). Hunt, E. B. (1966). Experiment in Induction. Ian H. Witten, E. F. (2005). ). Morgan Kaufmann. Jaime G. Carbonell, R. S. (1983). Machine Learning: A Historical and Methodological Analysis. Association for the Advancement of Artificial Intelligence , 4 (3), 1-10.

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