KDD'99 competition
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TL;DR
In this paper, exploratory data analysis reveals unusual data anomalies; a two-stage prediction model yields superior results those obtained in the 1998 competition; a decision tree better understand the model (the decision boundary); and a confidence interval is applied to establish a range upon which to reasonably judge model performance.
Abstract
In this paper, we expand on the 1998 KDD cup competition findings: exploratory data analysis reveals unusual data anomalies; a two-stage prediction model yields superior results those obtained in the 1998 competition; we use a decision tree better understand the model (the decision boundary); and we apply a confidence interval to establish a range upon which we can reasonably judge model performance.