Most packages concentrate either on machine learning or a specific subset of visualization techniques. Few packages effectively integrate both visualization and machine learning. This paper will discuss how, if possible a visualization technique can suggest a machine learning technique. The complementary function of verifying a machine learning result by a particular visualization will also be discussed . It seems that many Neural Net packages have ways to visualize the weights in a network, and possibly to give some insight to which input features are most important in a network.
Some packages try and visualize learned network function by a mapping down to two dimensions.
This paper will research these visualization methods. Assuming some visualizations work better for certain functions, this method is only limited by the particular visualization used, not the neural network. In the same manner complicated rule based classifications can be visualized. Exploring Large Multidimensional Data Sets, IEEE Visualization'96 Proceedings, Hot Topic, San Francisco, CA, 1996. A tool for viewing multidimensional data.