Description: 自己编的特征选择程序，分别包括用顺序前进法(SFS),顺序后退法(SBS),增l 减r 法(l–r)、SFFS法进行选择的程序-own addendum to the feature selection procedures, including the use of sequential forward (SFS). back order (SBS), by reducing r l (l-r), SFFS method to choose the procedure Platform: |
Size: 4096 |
Author:夏玉 |
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Description: 特征选择算法的改进．．．比较实践证明是个优秀的算法-feature selection algorithm improvements. . . Practice has proved that it is more an outstanding Algorithm Platform: |
Size: 2048 |
Author:陈孟 |
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Description: Feature selection is a preprocessing technique frequently used in data mining and machine learning tasks. It can reduce dimensionality, remove irrelevant data, increase learning accuracy, and improve results comprehensibility. FCBF is a fast correlation-based filter algorithm designed for high-dimensional data and has been shown effective in removing both irrelevant features and redundant features Platform: |
Size: 64512 |
Author:zhaoyingjie |
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Description: 经典的LDA特征选择算法，用matlab实现，包括数据集-LDA classic feature selection algorithm, using matlab to achieve, including a data set Platform: |
Size: 13312 |
Author:shall |
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Description: 针对SVM法线特征筛选算法仅考虑法线对特征筛选的贡献,而忽略了特征分布对特征筛选的贡献的不足,在对SVM法线算法进行分析的基础上,基于特征在正、负例中出现概率的不同提出了加权SVM法线算法,该算法考虑到了法线和特征的分布.通过试验可以看出,在使用较小的特征空间时,与SVM法线算法和信息增益算法相比,加权SVM法线算法具有更好的特征筛选性能.-Normal feature selection for SVM algorithm only considered normal for the contribution of feature selection, to the neglect of the characteristics of the distribution of feature selection have contributed to the lack of normal SVM algorithm based on the analysis, based on the characteristics of the positive and negative cases emergence of a different probability-weighted normal SVM algorithm, which takes into account the distribution and characteristics of normal. through the test can be seen in the use of smaller feature space, the normal and the SVM algorithm and information gain algorithm, normal weighted SVM algorithm has better performance of feature selection. Platform: |
Size: 4096 |
Author:苏苏 |
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Description: AdaBoost is an efficient tool in machine learning. It can combine a series of weak learners into a strong learner. Besides pattern classification, it also can be applied into feature selection. This document explains the use of AdaBoost. Platform: |
Size: 1152000 |
Author:njustyw |
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Description: 利用最小互信息实现向量的特征选择，优化分类器的设计，原创-The use of mutual information to achieve the smallest feature selection vectors, optimizing the classifier design, originality Platform: |
Size: 1024 |
Author:王将 |
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Description: 关于链式智能体遗传算法用于数值优化和特征选择的论文，可以与我联系相互交流-On the chain-agent genetic algorithm for numerical optimization and feature selection of the papers, you can contact me exchange Platform: |
Size: 1073152 |
Author:李明 |
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Description: 这个程序实现了Francis R. Bach的Bolasso算法，用于特征选取和预测。主要用于高纬度问题的特征选取，它使用了带有Bootstrap方法的自助抽样的正则化回归，并使用了Karl Skoglund的lars实现。-This procedure achieved Francis R. Bach s Bolasso algorithms for feature selection and forecasting. The main problem for high-latitude feature selection, it uses a method of self-help Bootstrap sampling Tikhonov reunification, and Karl Skoglund used to achieve the lars. Platform: |
Size: 198656 |
Author:xuechaoling |
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Description: 协同模糊聚类建模通过特征选择和协同模糊聚类的模糊建模方法构建T-S模型，并用此模型对数据进行测试。-Collaborative fuzzy clustering modeling and collaboration through the feature selection fuzzy clustering TS fuzzy modeling method to build models and use this model of data for testing. Platform: |
Size: 3072 |
Author:zhangwenming |
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Description: feature selection from iris data set it will use statistical methods and get the best set of features then use graphs to classify the data-feature selection from iris data set it will use statistical methods and get the best set of features then use graphs to classify the data Platform: |
Size: 28672 |
Author:madurangak |
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Description: It's a Matlab toolbox designed by ASU. It is easy to use and you can use it to achieve the feature selection, classify and so on. Platform: |
Size: 8908800 |
Author:liang911
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Search - FEATURE SELECTION