Depth = 4 and number = 4 seems to work well for this data. Other parameters include the feature importance type, for example: gain, weight, cover, total_gain or total_cover. These can be tuned ...

[Click on image for larger view.] Figure 1: AdaBoost Binary Classification for Spam Detection in Action The AdaBoost model requires only one parameter, the number of weak learners to use. The demo ...

you would have to use a Dataset definition that more closely resembles one designed for multi-class classification than for binary classification. The example code presented in this article can be ...

This paper revisits the question of what is really important for strong long-term growth by using a Binary Classification Tree approach, a nonparametric statistical technique that is not commonly used ...

The variables center, treatment, sex, and baseline (baseline respiratory status) are classification variables with two levels. The variable age (age at time of entry into the study) is a continuous ...