While this data mining project has been fun, it has also has been frustrating. For reasons discussed previously, there is a fine line between having too much data and not enough data. This issue becomes complicated by the fact that all the data points are measurements, thus are significant. This may be an ambigous case, where the amount of data removed from the record does not affect the accuracy of the model.
However, despite these issues, it has been enjoyable trying to find patterns where the patterns may or may not exist. Using a data mining tool like RapidMiner, in the very least, adds to my skillset as a programmer and now knowledge discoverer.