Файл:6584-efficient-high-order-interaction-aware-feature-selection-based-on-conditional-mutual-information.pdf

Материал из Материалы по машинному обучению
Перейти к: навигация, поиск
6584-efficient-high-order-interaction-aware-feature-selection-based-on-conditional-mutual-information.pdf(0 × 0 пикселей, размер файла: 581 КБ, MIME-тип: application/pdf)

Alexander Shishkin,Anastasia Bezzubtseva, Alexey Drutsa, Ilia Shishkov, Ekaterina Gladkikh, Gleb Gusev, Pavel Serdyukov

Yandex; 16 Leo Tolstoy St., Moscow 119021, Russia {sisoid,nstbezz,adrutsa,ishfb,kglad,gleb57,pavser}@yandex-team.ru

Abstract

This study introduces a novel feature selection approach CMICOT, which is a further evolution of filter methods with sequential forward selection (SFS) whose scoring functions are based on conditional mutual information (MI). We state and study a novel saddle point (max-min) optimization problem to build a scoring function that is able to identify joint interactions between several features. This method fills the gap of MI-based SFS techniques with high-order dependencies. In this high-dimensional case, the estimation of MI has prohibitively high sample complexity. We mitigate this cost using a greedy approximation and binary representatives what makes our technique able to be effectively used. The superiority of our approach is demonstrated by comparison with recently proposed interactionaware filters and several interaction-agnostic state-of-the-art ones on ten publicly available benchmark datasets.

История файла

Нажмите на дату/время, чтобы просмотреть, как тогда выглядел файл.

Дата/времяРазмерыУчастникПримечание
текущий12:04, 28 декабря 20160 × 0 (581 КБ)Slikos (обсуждение | вклад)
  • Вы не можете перезаписать этот файл.

Следующая 1 страница ссылается на данный файл: