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Feature Selection using Matlab.
The DEMO includes 5 feature selection algorithms:
• Sequential Forward Selection (SFS)
• Sequential Floating Forward Selection (SFFS)
• Sequential Backward Selection (SBS)
• Se
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Neighborhood rough set based heterogeneous feature subset selection
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sar is a Rough Set-based Attribute Reduction (aka Feature Selection) implementation. This is an implementation of ideas described, among other places, in the following paper:
Qiang Shen and Alexios Chouchoulas, A Modular Approach to Generating Fu
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A distributed PSOSVM hybrid system with feature selection and parameter optimization
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This study proposed a novel PSO–SVM model that hybridized the particle swarm optimization (PSO) and support vector machines (SVM) to
improve the clas
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基于粗糙集的特征子集筛选的一种算法-Based on rough set feature subset selection of an algorithm! ! !
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针对目标与背景两类图像模式识别问题,在已有的特征选择方法基础上,提出了一种新颖的基于免疫分子编码机理的图像特征选择方法(IACA). 该方法借鉴生物免疫系统的抗体分
子编码机理,在对样本进行参数估计情况下,提出熵度量单个特征对于目标和背景的识别敏感度 从集合的角度研究并且定义了特征之间的包含和互补关系 并且基于组成抗体分子氨基酸结合能量最小原则,提出了关于图像目标的免疫抗体构建规则 最终实现了寻找最优特征子集的算法IACA ,该特征子集的维数通过算法自动获得无需人为设定,选择结果为目标的“免
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Support Vector Machines, one of the new techniques for pattern classifi cation, have been widely used in many application areas. The kernel
parameters setting for SVM in a training process impacts on the classifi cation accuracy. Feature
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特征提取方面。文章An adaptive multiple feature subset method for feature ranking and feature selection的实现源代码。-An adaptive multiple feature subset method for feature ranking and feature selection
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eature selection, also known as variable selection, attribute selection or variable subset selection, is the process of selecting a subset of relevant features for use in model construction
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This a one of the data mining algorithm completly made by me. This is based on feature subset selection. One of the popular algorithm of feature selection named Fast Correlation based feature selection algorithm(FCBF).It s complete code is here with
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this code is for Feature subset selection using differential evolution and and was written by language matlab .-this code is for Feature subset selection using differential evolution and and was written by language matlab .
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这是一种基于近红外光谱的非线性建模方法及系统，从各所述近红外光谱数据随机挑出一部分作为校正集，挑出一部分作为验证集；将所述校正集和所述验证集通过主成分分析得到光谱特征空间；在所述光谱特征空间中，通过马氏距离法选取所述校正集里与所述验证集的各个样本最近似的样本作为校正子集；从所述校正子集中提取主成分数，作为BP神经网络的输入层建立回归模型，不仅能解决各因素之间多重相关的问题，还避免了大量的噪声和一些无用的信息，降低了变量维数，在BP神经网络的非线性映射能力和适应学习能力的基础上，提高了模型的预测稳
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Feature subset selection
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feature subset selection methods
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This paper presents an online feature selection algorithm
for video object tracking. Using the object and background
pixels from the previous frame as training samples, we model the
feature selection problem as finding a good subset of features to
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