classification ensemble, which uses the weighed polling of outputs, is the art of combining a set of basic classifiers for generating high-performance, robust and more stable results. this study aims to improve the results of identifying the persian handwritten letters using error correcting output coding (ecoc) ensemble method. furthermore, the feature selection is used to reduce the costs of ...

We consider the variable selection problem, which seeks to identify important variables influencing a response Y out of many candidate features X1, . . . , Xp. We wish to do so while offering finite-sample guarantees about the fraction of false positives—selected variables Xj that in fact have no effect on Y after the other features are known. When the number of features p is large (perhaps eve...

since most common form of cervical cancer starts with pre-cancerous changes, a flawless detection of these changes becomes an important issue to prevent and treat the cervix cancer. there are 2 ways to stop this disease from developing. one way is to find and treat pre-cancers before they become true cancers, and the other is to prevent the pre-cancers in the first place. the presented approach...

different approaches have been proposed for feature selection to obtain suitable features subset among all features. these methods search feature space for feature subsets which satisfies some criteria or optimizes several objective functions. the objective functions are divided into two main groups: filter and wrapper methods.  in filter methods, features subsets are selected due to some measu...

objectives: genetic polymorphism interactions are among the important factors in affliction with complex diseases like alzheimer’s disease. the important goal of genetic association studies is to identify a combination of polymorphisms and measure their importance in increasing the risk of occurrence of such diseases. in this study, feature selection approach of logic regression was used to ide...

a full investigation into the features extracted from voice signals of people with and without parkinson’s disease was performed. a total of 31 people with and without the disease participated in the data collection phase. their voice signals were recorded and processed. the relevant features were then extracted. a variety of feature selection methods have been utilized resulting in a good perf...

Sentiment analysis means to extract opinion of users from review documents. Sentiment classification using Machine Learning (ML) methods faces the problem of high dimensionality of feature vector. Therefore, a feature selection method is required to eliminate the irrelevant and noisy features from the feature vector for efficient working of ML algorithms. Rough Set Theory based feature selectio...