Important Features Detection in Continuous Data
نویسندگان
چکیده
منابع مشابه
Important Features Detection in Continuous Data
In this paper, a method for calculating the importance factor of continuous features from a given set of patterns is presented. A real problem in many practical cases, like medical data, is to find which parts of patterns are crucial for correct classification. This leads to the need of preprocessing all data, which has influence on both time and accuracy of applied methods (when unimportant da...
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هدف از این تحقیق، ارزیابی و بهبود متریک های موجود جهت تایید صحت نقشه های قدیمی سه بعدی برداری با استفاده از ابر نقطه حاصل از لیزر اسکن جدید شهر اصفهان می باشد . بنابراین ابر نقطه حاصل از لیزر اسکنر با چگالی حدودا سه نقطه در هر متر مربع جهت شناسایی عوارض تغییر کرده در نقشه های قدیمی سه بعدی استفاده شده است. تمرکز ما در این تحقیق بر روی ساختمان به عنوان یکی از اصلی ترین عارضه های شهری می باشد. من...
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Isolating relevant information and reducing the dimensionality of the original dataset are key areas of interest in pattern recognition and machine learning. In this paper a novel approach to reducing dimensionality of the feature space by employing independent component analysis (ICA) is introduced. While ICA is primarily a feature extraction technique, it is used here as a feature selection/c...
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ژورنال
عنوان ژورنال: International Journal of Advanced Computer Science and Applications
سال: 2012
ISSN: 2158-107X,2156-5570
DOI: 10.14569/ijacsa.2012.031239