Читать книгу Advanced Healthcare Systems - Группа авторов - Страница 48

This algorithm used the divide-and-conquer method to construct a decision tree to solve the classification problem using decision-making trees [8]. These form a model based on decisions that relate to features in the data set and very fast to train. Examples of these types of models include random forests and conditional decision trees. The goal is to create a model that predicts the accuracy of thyroid disease using target variables, i.e., TSH by using simple decision rules derived from data features, i.e., T3 and T4.

This algorithm works on the basis of input and output variable (x, y) that is specified in a label set of pairs as follows.

The algorithm is to learn the mapping function from the input variable x to the output variable y, which is given the label set of the input output pair

(3.1)

In Equation (3.1), T represents the training set and n represents the number of training samples.