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Biomedical datasets usually include a large number of features relative to the number of samples. However, some data dimensions may be less relevant or even irrelevant to the output class. Selection of an optimal subset of features is critical, not only to reduce the processing cost but also to improve the classification results. To this end, this paper presents a hybrid method of filter and wr...

One of the most important artificial immune algorithms is negative selection algorithm, which is an anomaly detection and pattern recognition technique; however, recent research has shown the successful application of this algorithm in data classification. Most of the negative selection methods consider deterministic boundaries to distinguish between self and non-self-spaces. In this paper, two...

several techniques exist to select and materialize a proper set of data in a suitable structure that manage the queries submitted to the online analytical processing systems. these techniques are called view management techniques, which consist of three research areas: 1) view selection to materialize, 2) query processing and rewriting using the materialized views, and 3) maintaining materializ...

the existing literature on bantu verbal semantics demonstrated that inherent semantic content of verbs pairs directly with the selection of tense, aspect and modality formatives in bantu languages like chasu, lucazi, lusamia, and shiyeyi. thus, the gist of this paper is the articulation of semantic classification of verbs in kiswahili based on the selection of tam types. this is because the sem...

the stock evaluation process plays an important role in portfolio selection because it is the prerequisite for investment and directly influences on the stock allocation. this paper presents a methodology based on data envelopment analysis for portfolio selection, decision making units which can be stocks or other financial assets. first, dmus efficiencies are computed based on input/output com...