We introduce a new method of feature selection for text categorization. Our MMR-based feature selection method strives to reduce redundancy between features while maintaining information gain in selecting appropriate features for text categorization. Empirical results show that MMR-based feature selection is more effective than Koller & Sahami’s method, which is one of greedy feature selection ...

Feature selection is a popular topic. The main approaches to deal with it fall into the three categories of filters, wrappers and embedded methods. Advancement in algorithms, though proving fruitful, may be not enough. We propose integrate an explainable AI approach, based on Shapley values, provide more accurate information for feature selection. test our proposal real setting, which concerns ...

Data mining is related to large number of databases. Dealing with such large number of datasets may create some obstacles. Such problems can be avoided by using feature selection Technique. Feature selection Technique is a method which selects an optimal subset from original feature set. The implementation is done by removing repetitive features. The underlying structure has been neglected by t...

37 Abstract — Feature selection (FS) is considered to be an important preprocessing step in machine learning and pattern recognition, and feature evaluation is the key issue for constructing a feature selection algorithm. Feature selection process can also reduce noise and this way enhance the classification accuracy. In this article, feature selection method based on ∩ fuzzy similarity measure...

In our previous work, we have developed the backward feature selection method based on class regions approximated by ellipsoids. In this paper, we accelerate feature selection by the forward selection search, the symmetric Cholesky factorization, and deletion of duplicated calculations between consecutive factorizations. The feature selection for two data sets shows that our method is faster th...

Multi-label feature selection is regarded as one of the most promising techniques that can be used to maximize the efficacy and efficiency of multi-label classification. However, because multi-label feature selection algorithms must consider multiple labels concurrently, the task is more difficult than singlelabel feature selection tasks. In this paper, we propose the Mutual Information-based m...

An important step in the analysis of high-dimensional biomedical data is feature selection. Typically, a feature subset selected by a feature selection method is evaluated for relevance towards a task such as prediction or classification. Another important property of a feature selection method is stability that refers to robustness of the selected features to perturbations in the data. In biom...

this paper demonstrates design and fabrication o f a mechatronic system for human drowsiness detection. this system can be used in multiple places. for example, in factories, it is used on some dangerous machinery and in cars in order t o prevent the operator o r driver from falling asleep. this system is composed of three parts: (1) mechanical, (2) electrical and (3) image processing system. a...

breast cancer is the most common type of cancer among women. the important key to treat the breast cancer is early detection of it because according to many pathological studies more than 80% of all abnormalities are still benign at primary stages; so in recent years, many studies and extensive research done to early detection of breast cancer with higher precision and accuracy.infra-red breast...