By Ian H. Witten
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Extra resources for Data Mining: Practical Machine Learning Tools and Techniques With Java Implementations
The main() method accepts the following command-line arguments: the name of a message file (given by –m), the name of a file holding an object of class MessageClassifier (–t) and, optionally, the classification of the message (–c). The message’s class can be hit or miss. If the user provides a classification using –c, the message will be added to the training data; if not, the program will classify the message as either hit or miss. Main() The main() method reads the message into an array of characters and checks whether the user has provided a classification for it.
There are two types of evaluators that you can specify with –E: ones that consider one attribute at a time, and ones that consider sets of attributes together. attributeSelection. attributeSelection. InfoGainAttributeEval, which evaluates attributes according to their information gain. attributeSelection. CfsSubsetEval, which evaluates subsets of features by the correlation among them. If you give the name of a subclass of AttributeEvaluator, you must also provide, using –T, a threshold by which the filter can discard low-scoring attributes.
By default all instances are deleted that exhibit one of a given set of nominal attribute values (if the specified attribute is nominal), or a numeric value below a given threshold (if it is numeric). However, the matching criterion can be inverted using –V. The SwapAttributeValuesFilter is a simple one: all it does is swap the positions of two values of a nominal attribute. Of course, this could also be accomplished by editing the ARFF file in a word processor. The order of attribute values is entirely cosmetic: it does not affect machine learning at all.