원문정보
초록
영어
Feature selection has become very vital aspect in musical instruments sounds for handling the problem of ‘curse of dimensionality’. Various feature selection techniques have been applied in this domain focusing on Western musical instruments sounds. However, study on feature selection using rough sets of non-Western musical instruments sounds including Malay Traditional musical instruments is inadequate and still needs an intensive research. Thus, in this paper, an alternative feature selection technique using rough set theory based on Maximum Degree of dependency of Attributes (MDA) technique for Traditional Malay musical instruments sounds is proposed. The modeling process comprises eight phases: data acquisition, sound editing, data representation, feature extraction, data discretization, data cleansing, feature selection using proposed technique and feature validation via classification. The results show that the performance of the best 17 selected features is increase up to 99.82% and 98.03% with 1-NN and PART classifiers respectively.
목차
1. Introduction
2. Related Works
3. Rough Set Theory
3.1. Information System
3.2. Indiscernibility Relation
3.3. Set Approximations
3.4. Dependency of Attributes
3.5. Reducts and Core
4. The Modeling Process
4.1. Data Acquisition, Sound Editing, Data Representation and Feature Extraction
4.2. Data Discretization
4.3. Data Cleansing using Rough Set
4.4. The Proposed Technique
4.5. Feature Evaluation via Classification
5. Results and Discussion
6. Conclusion
References