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Modified Reduct: Nearest Neighbor Classification

机译:修正折减法:最近的邻居分类

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摘要

Dimension reduction of data is an important theme as in the data processing and on the web to represent and manipulate higher dimensional data. Rough set developed is fundamental and useful to process higher dimensional data. Reduct in the rough set is a minimal subset of features, which has almost the same discernible power as the entire features in the higher dimensional scheme. Then, there are relations between reducts and their classification classes. Here, we develop a method which connects reducts and the nearest neighbor method to classify data with higher classification accuracy. To improve the classification ability of reducts, we propose a new modified reduct and its optimization method for the classification with higher accuracy. Then, it is shown that the modified reduct improves the classification accuracy, which is followed by the optimized nearest neighbor classification.
机译:数据降维是数据处理和Web上代表和处理高维数据的重要主题。开发的粗糙集对于处理高维数据非常重要。粗糙集中的约简是特征的最小子集,其具有与高维方案中的整个特征几乎相同的可分辨能力。然后,归约及其分类类别之间存在关系。在这里,我们开发了一种方法,该方法将归约法和最近邻法联系起来,以更高的分类精度对数据进行分类。为了提高归类的分类能力,我们提出了一种新的改进归类及其优化方法,用于分类的准确度更高。然后,表明改进的归约方法提高了分类精度,随后是优化的最近邻分类。

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