ClasserScript Interface to Classer Toolkit:
ClasserScript is a batch interface to the Classer toolkit. More specifically, ClasserScript is a miniature language; it lets you define views of data, classifier models, and iterative combinations of the two to generate a variety of output metrics.
ClasserScript offers a simple environment for doing ARTMAP-based research without having to write any code. It lets you script simulations, preprocess data, and generate performance metrics that can be used in tuning an ARTMAP classifier.
ClasserScript Software:
The ClasserScript executable, csd, ("ClasserScript Driver") is available here.
Documentation
The ClasserScript User Guide (v1.1) is a comprehensive introduction to using ClasserScript, and more generally, to the Classer toolkit.
The User's Guide includes:
Scripts Cookbook:
The following set of scripts provides a cookbook of examples to help you get started with ClasserScript's basic functionality. The data sets must be downloaded before the scripts can be used. In addition, unless you install the data sets at the top directory level, you will need to rename their locations in the scripts.
| Script Name | Data set | Notes |
| loadData | Boston | Demonstrates advantage of binary representation for large data sets |
| showData | Boston | Generates six images from the data set, storing them in bosImg?.ppm |
| basicPrints | CIS | Prints memory size, timing, number of F2 nodes |
| printCmat | Letters (CV) | Good performance (96.9%), 5x5 cross-validation, confusion matrix printout |
| foreach | CIS (CV) | Prints timing and percent correct for 100 vigilance values |
| foreach2D | Letters (CV) | Tabular printout, exploring 2D parameter space |
| setFeatures(1) | Letters | Features 1-11, poor performance (78%) |
| setFeatures(2) | Letters | Features 3-13, medium performance (49%) |
| setFeatures(3) | Letters | Features 6-16, good performance (92%) |
| setVigilance | CIS (CV) | 3 vigilance values, increasing performance & memory |
| setVoters | CIS (CV) | 1, 3, 5 voters, increasing performance & memory |
| outputCmat | Letters | Graphical confusion matrix ᎂ cmPlot.pgm |
| outputPred | Letters | Graphical prediction plot ᎂ lettersPred.ppm |
| thematic | Boston | Train GT, classify all, fuzzy ARTMAP, cap=268 ᎂ mapThematic.ppm |
| bosCv | Boston | Demonstrates cross-validation with user-specified partitions |