Recent advances in sensor technology opened new possibilities for remote sensing. For example, the appearance of sensor higher spatial and spectral resolution. In terms of spectral resolution, the number of available bands increased significantly, resulting in hyperspectral sensors. Hyperspectral remote sensing images are characterized by the division of the electromagnetic spectrum in a great ...

Fuzzy rule-based models have been extensively used in regression problems. Besides high accuracy, one of the most appreciated characteristics of these models is their interpretability, which is generally measured in terms of complexity. Complexity is affected by the number of features used for generating the model: the lower the number of features, the lower the complexity. Feature selection ca...

The exact forecast of heart disease is necessary to proficiently treating cardiovascular patients before a failure happens. Assuming we talk about artificial intelligence (AI) techniques, can be accomplished utilizing an ideal AI model with rich medical services information on diseases. To begin with, the feature extraction technique, gradient boosting-based sequential selection (GBSFS) applied...

Objective(s): This study addresses feature selection for breast cancer diagnosis. The present process uses a wrapper approach using GA-based on feature selection and PS-classifier. The results of experiment show that the proposed model is comparable to the other models on Wisconsin breast cancer datasets. Materials and Methods: To evaluate effectiveness of proposed feature selection method, we ...

There are a lot of problems that arise in the process of building a brain-computer interface based on electroencephalographic signals (EEG). A huge imbalance between a number of experiments possible to conduct and the size of feature space, containing features extracted from recorded signals, is one of them. To reduce this imbalance, it is necessary to apply methods for feature selection. One o...

Though Fisher score is a representative and effective feature selection method, it has an unsolved drawback: it either evaluates the features individually and selects the top features, or selects features using the sequential search strategies. The individual-method ignores the mutual relationship among the selected features while the sequential-methods always suffer from heavy computation. In ...

In this paper a feature selection algorithm CSSFFS (Constrained search sequential floating forward search) based on SVM is proposed for detecting breast cancer. It is a greedy algorithm with search strategy of constrained search. The aim of this algorithm is to achieve a feature subset with minimal BER (Balanced error rate). This is a hybrid algorithm with the combination of filters and wrapper...