A Two-Phase Approach for Semi-Supervised Feature Selection
نویسندگان
چکیده
منابع مشابه
Forward Semi-supervised Feature Selection
Traditionally, feature selection methods work directly on labeled examples. However, the availability of labeled examples cannot be taken for granted for many real world applications, such as medical diagnosis, forensic science, fraud detection, etc, where labeled examples are hard to find. This practical problem calls the need for “semi-supervised feature selection” to choose the optimal set o...
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With the continued and relentless growth in dataset sizes in recent times, feature or attribute selection has become a necessary step in tackling the resultant intractability. Indeed, as the number of dimensions increases, the number of corresponding data instances required in order to generate accurate models increases exponentially. Fuzzy-rough set-based feature selection techniques offer gre...
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ژورنال
عنوان ژورنال: Algorithms
سال: 2020
ISSN: 1999-4893
DOI: 10.3390/a13090215