Course: More Data Mining with Weka

Try this (instead of a quiz). Market basket analysis aims to discover interesting purchasing patterns in large datasets of transactional records. Typically these are the contents of individual shoppers’ baskets …

Apriori’s strategy for generating association rules is to specify a minimum “confidence” and iteratively reduce “support” until enough rules are found. Doing this efficiently involves an interesting and subtle algorithm. …

Association rule learners find associations between attributes. Between any attributes: there’s no particular class attribute. Rules can predict any attribute, or indeed any combination of attributes. To find them we …

Here are a couple of schemes for rule learning. The first, called PART, is a way of forming rules from partial decision trees. The second, called Ripper (JRip in Weka), …

Before attempting the quiz that follows, you will need to download Weka’s PRISM package. We explained Weka’s “package” system in the previous course Data Mining with Weka. Here’s a refresher. …

Any decision tree has an equivalent set of rules … and any rule set has an equivalent decision tree. So they’re the same? It’s not so simple. If you read …

Naive Bayes has three flaws when applied to document classification. First, a word’s non-appearance counts just as much its appearance, whereas surely a document’s class is determined by the words …

In the last lesson we encountered a two-class dataset where the accuracy on one class was high and the accuracy on the other was low. Because the first class contained …

A document classification problem can be represented in the ARFF format with two attributes per instance, the document text in a “string” attribute and the document class as a nominal …

Converting numeric attributes to nominal is called “discretization”. But wait! Why would you want to do this? Well, for one thing, some machine learning methods only work on nominal attributes. …

Document classification is a popular and important application of data mining. But how can it be done? Weka allows string attributes, and it’s simple to load an entire document into …

J48 effectively discretizes numeric attributes as it goes along, which sounds good because split points are chosen in a local context, taking into account just the instances that reach that …

“Supervised” discretization methods take the class into account when setting discretization boundaries, which is often a very good thing to do. But wait! You mustn’t use the test data when …

Discretizing is transforming numeric attributes to nominal. You might want to do that in order to use a classification method that can’t handle numeric attributes (unlikely), or to produce better …

What is “big data” anyway? The term is typically used to refer to data sets that are so large that data mining tools have difficulty in dealing with them. But …