摘要
由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-调查人员发布了关于支持向量机的新报告。据新闻报道来自印度德拉敦，由Ne wsRx通讯员撰写，研究称：“在这项研究中，我们介绍了并对一种新的特征提取技术进行了评价,该技术分析了字符图像b的范围提高识别精度。该方法在最近邻(NN)的合取上进行了评估和支持向量机(SVM)分类器，并与各种特征选择方法进行比较包括基于一致性的分析(CBA)、相关特征集(CFS)、卡方属性(CSA)、独立成分分析(ICA)，潜在语义分析(LSA)，主成分分析(PCA)，以及随机投影(RP)。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Investigators publish new report on Su pport Vector Machines. According to newsoriginating from Dehradun, India, by Ne wsRx correspondents, research stated, “In this study, we introduceand assess a novel feature extraction technique that analyzes the extent of character image b oundariesto enhance recognition accuracy. This method is evaluated in conjuncti on with Nearest Neighbors (NN)and Support Vector Machine (SVM) classifiers, and compared against various feature selection methodsincluding Consistency Based Analysis (CBA), Correlation Feature Set (CFS), Chi-Squared Attribute (CSA),Inde pendent Component Analysis (ICA), Latent Semantic Analysis (LSA), Principal Comp onent Analysis(PCA), and Random Projection (RP).”
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