New explanation of boosting efficiency in classification problem

We study the reasons of high efficiency of methods based on classifiers compositions, such as boosting. It has been shown that one of the main grounds for such efficiency is the usage of the effect of independence of features. To investigate the performance of a method we run it directly on the distributions. We compare approximating capabilities of boosting and splines. Also we show the relation between a complexity and a margin.