MOFSRank: A Multiobjective Evolutionary Algorithm for Feature Selection in Learning to Rank
نویسندگان
چکیده
منابع مشابه
A Multiobjective Genetic Algorithm for Feature Selection in Data Mining
The rapid advance of computer based highthroughput technique have provided unparalleled opportunities for humans to expand capabilities in production, services, communications, and research. Meanwhile, immense quantities of high-dimensional data are accumulated challenging state-of-the-art data mining techniques .The intelligent analysis of Databases may be affected by the presence of unimporta...
متن کاملSequential and Mixed Genetic Algorithm and Learning Automata (SGALA, MGALA) for Feature Selection in QSAR
Feature selection is of great importance in Quantitative Structure-Activity Relationship (QSAR) analysis. This problem has been solved using some meta-heuristic algorithms such as: GA, PSO, ACO, SA and so on. In this work two novel hybrid meta-heuristic algorithms i.e. Sequential GA and LA (SGALA) and Mixed GA and LA (MGALA), which are based on Genetic algorithm and learning automata for QSAR f...
متن کاملSequential and Mixed Genetic Algorithm and Learning Automata (SGALA, MGALA) for Feature Selection in QSAR
Feature selection is of great importance in Quantitative Structure-Activity Relationship (QSAR) analysis. This problem has been solved using some meta-heuristic algorithms such as: GA, PSO, ACO, SA and so on. In this work two novel hybrid meta-heuristic algorithms i.e. Sequential GA and LA (SGALA) and Mixed GA and LA (MGALA), which are based on Genetic algorithm and learning automata for QSAR f...
متن کاملLow-rank Feature Selection for Reinforcement Learning
Linear value function approximation is a common approach to solving large reinforcement learning problems. Because designing good approximation features is difficult, automatic feature selection is an important research topic. We propose a new method for feature selection, which is based on a low-rank factorization of the transition matrix. Our approach derives features directly from high-dimen...
متن کاملFast SFFS-Based Algorithm for Feature Selection in Biomedical Datasets
Biomedical datasets usually include a large number of features relative to the number of samples. However, some data dimensions may be less relevant or even irrelevant to the output class. Selection of an optimal subset of features is critical, not only to reduce the processing cost but also to improve the classification results. To this end, this paper presents a hybrid method of filter and wr...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Complexity
سال: 2018
ISSN: 1076-2787,1099-0526
DOI: 10.1155/2018/7837696