ABSTRACT
At the University of California, San Diego Medical Center, when a heart attack patient is admitted, 19 variables are measured during the first 24 hours. These include blood pressure, age, and 17 other ordered and binary variables summarizing the medical symptoms considered as important indicators of the patient's condition. The measurements are made on many meteorological variables, such as temperature, humidity, upper atmospheric conditions, and on the current levels of a number of airborne pollutants. In systematic classifier construction, past experience is summarized by a learning sample. This consists of the measurement data on N cases observed in the past together with their actual classification. Depending on the problem, the basic purpose of a classification study can be either to produce an accurate classifier or to uncover the predictive structure of the problem. The major guide that has been used in the construction of classifiers is the concept of the Bayes rule.
