2016
DOI: 10.5815/ijisa.2016.01.08
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Dimensionality Reduction using Genetic Algorithm for Improving Accuracy in Medical Diagnosis

Abstract: Abstract-The technological growth generates the massive data in all the fields. Classifying these highdimensional data is a challenging task among the researchers. The high-dimensionality is reduced by a technique is known as attribute reduction or feature selection. This paper proposes a genetic algorithm (GA)-based features selection to improve the accuracy of medical data classification. The main purpose of the proposed method is to select the significant feature subset which gives the higher classification… Show more

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Cited by 33 publications
(19 citation statements)
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“…They are based on natural genetics and natural selection [12]. GAs begin with a rando mly generated set of candidate solutions or chromosomes which form a population.…”
Section: Genetic Algorithm Geneticmentioning
confidence: 99%
“…They are based on natural genetics and natural selection [12]. GAs begin with a rando mly generated set of candidate solutions or chromosomes which form a population.…”
Section: Genetic Algorithm Geneticmentioning
confidence: 99%
“…GA is noted to reduce not only the cost and computation time of the diagnostic process, but the proposed approach also improved the accuracy of classification. Reference [19] used a genetic algorithm (GA)-based features selection to improve the accuracy of medical data classification. The proposed genetic algorithm-based feature selection removes the irrelevant features and selects the relevant features from original dataset in order to improve the performance of the classifiers in terms of time to build the model, reduced dimension and increased accuracy.…”
Section: Intelligent Systems For Disease Diagnosismentioning
confidence: 99%
“…In presenting objects by linear method on the plane will select two numerical scales for mapping to them descriptions of objects with features in () Xn using functional 12 (8), which are used for mapping objects of 0 E in two numerical scales. It is proved the equivalence of these two scales by (2) in [10].…”
Section: Problem Statementmentioning
confidence: 99%
“…Searching informative features set usually be used to estimate the classification accuracy of the algorithms. In [8] a genetic algorithm (GA)-based features selection to improve the accuracy of medical data classification is proposed. In [9] developed a novel feature selection technique based on the Partial Least Squares (PLS).…”
Section: Introductionmentioning
confidence: 99%