Description: 提出了一种基于支持向量机的多类模拟调制方式识别算法。该算法通过分析模拟调制信号的特点，提取有效的特征向量以区分不同的调制方式，并基于支持向量机和判决树分类思想，将特征向量映射到高维空间中加以分类。-A support vector machine based on the many types of analog modulation recognition algorithm. The algorithm by analyzing the characteristics of analog modulation signal to extract effective feature vector in order to distinguish between different modulation methods, and based on support vector machines and decision tree classification of ideas, will feature vector is mapped to the high-dimensional space to be classified. Platform: |
Size: 224256 |
Author:zhaoxiufen |
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Description: 包含了很多分类算法，有SVM，knn，决策树等，还有文档说明-Contains a lot of classification algorithms, there is SVM, knn, decision tree and so on, have documented Platform: |
Size: 990208 |
Author:来海锋 |
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Description: VM分类器通常具有较高的分类精度。我这里不想过多的去说SVM是怎么回事，只是提供一种使用SVM进行判别的方法。决策树与SVM的结合，可以分多类。-VM classifier usually has a higher classification accuracy. I do not want too much here to say how the matter SVM, SVM is used to provide a method for identification. The combination of decision tree and SVM, can be divided into many types. Platform: |
Size: 105472 |
Author:steve |
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Description: /*
The sample demonstrates how to build a decision tree for classifying mushrooms.
It uses the sample base agaricus-lepiota.data from UCI Repository, here is the link:
Newman, D.J. & Hettich, S. & Blake, C.L. & Merz, C.J. (1998).
UCI Repository of machine learning databases
[http://www.ics.uci.edu/~mlearn/MLRepository.html].
Irvine, CA: University of California, Department of Information and Computer Science.
*/
// loads the mushroom database, which is a text file, containing
// one training sample per row, all the input variables and the output variable are categorical,
// the values are encoded by characters. Platform: |
Size: 4096 |
Author:tofighi |
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Description: 几篇关于SVM研究的相关论文，主要是关于支持向量机决策树方面的-Several related papers on the SVM research, mainly on the aspects of support vector machine decision tree Platform: |
Size: 4227072 |
Author:liuying |
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Description: 为了准确地对监控场景中的运动目标进行语义上的分类，提出了一种基于聚类的核主成分分析梯度方向直方图和二又决策树支持向量机的运动目标分类算法。-In order to accurately monitor the movement of scene targets semantic classification, the clustering based on kernel principal component analysis of gradient direction histograms, and two and a support vector machine decision tree classification algorithm of moving objects. Platform: |
Size: 544768 |
Author:piano |
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Description: 为了准确地对监控场景中的运动目标进行语义上的分类， 提出了一种基于聚类的核主成分分析梯度方向直方图和二叉决策树支持向量机的运动目标分类算法．利用背景减法提取运动目标前景区域， 并识别出潜在候选运动目标．利
用提出的基于聚类的核主成分分析的梯度直方图描述子提取候选运动目标的特征， 以较低维数的数据有效地描述运动目标的有效特征． 将提取的运动目标特征输入二叉决策树支持向量机， 实现多类目标的准确分类． 通过在不同视频序列上的实验验证， 提出的算法对运动目标进行较好地分类， 而且在运算速度方面较传统目标分类方法有了明显的提高． 实验结果证明了算法对运动目标分类具有较好的准确性 可靠性和鲁棒性．-For the purpose of semantically classifying moving objects accurately in a surveillance scene，a moving objects classification method based on the clustered kernel principal component analysis ( CKPCA) of the histogram
of oriented gradients ( HOG) and support vector machine ( SVM) was proposed． Firstly，the moving areas in the
foreground were extracted by means of the background subtraction method，and some of them were identified as potential candidates of moving objects． Secondly，the characteristics of the moving objects were obtained by the CKPCA- HOG descriptor，which could describe the moving objects＇ effective features at a lower data dimension． Finally，the data characteristics were fed into a binary SVM decision tree，and the final multi- class classification results were obtained accurately． After verifying different video sequences，the algorithm was able to classify moving targets very well． Compared with traditional classification methods，the proposed method makes obvious improv Platform: |
Size: 272384 |
Author:高峰 |
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Description: VM分类器通常具有较高的分类精度。我这里不想过多的去说SVM是怎么回事，，只是提供一种使用SVM进行判别的方法。决策树与SVM的结合，可以分多类。
-VM classifier usually has high classification accuracy. I do not want too much to say that SVM is how, just a SVM is used to discriminate. Combination of decision tree and SVM multi-class. Platform: |
Size: 106496 |
Author:获得 |
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Description: SVM算法的一个windows下实现，用决策树实现预测农产品质量，数据存放于SQLServer中，ADO方式存取。-SVM algorithm a windows with decision tree predictive quality of agricultural products, the data stored in SQLServer ADO accessed. Platform: |
Size: 26624 |
Author:铭泽 |
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Description: Face recognition in a fuzzy method. Contains SVM, LDA, decision tree and so on, the effect is very good, worthy of reference. Platform: |
Size: 270336 |
Author:张鹏 |
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Description: Face recognition in a fuzzy method. Contains SVM, LDA, decision tree and so on, the effect is very good, worthy of reference. Platform: |
Size: 697344 |
Author:张鹏 |
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Description: Face recognition in a fuzzy method. Contains SVM, LDA, decision tree and so on, the effect is very good, worthy of reference. Platform: |
Size: 75776 |
Author:张鹏 |
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Description: Face recognition in a fuzzy method. Contains SVM, LDA, decision tree and so on, the effect is very good, worthy of reference. Platform: |
Size: 266240 |
Author:张鹏 |
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Description: Face recognition in a fuzzy method. Contains SVM, LDA, decision tree and so on, the effect is very good, worthy of reference. Platform: |
Size: 424960 |
Author:张鹏 |
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Description: 本书共有43章，内容涵盖常见的神经网络（BP、RBF、SOM、Hopfield、Elman、LVQ、Kohonen、GRNN、NARX等）以及相关智能算法（SVM、决策树、随机森林、极限学习机等）。同时，部分章节也涉及了常见的优化算法（遗传算法、蚁群算法等）与神经网络的结合问题。此外，本书还介绍了MATLAB R2012b中神经网络工具箱的新增功能与特性，如神经网络并行计算、定制神经网络、神经网络高效编程等(This book consists of 43 chapters, covering common neural networks (BP, RBF, SOM, Hopfield, Elman, LVQ, Kohonen, GRNN, NARX, etc.) and related intelligent algorithms (SVM, decision tree, random forest, extreme learning machine, etc.). At the same time, some chapters also involve the combination of common optimization algorithms (genetic algorithm, ant colony algorithm, etc.) and neural networks. In addition, the book also introduces the new functions and characteristics of the neural network toolbox in MATLAB R2012b, such as parallel computing of neural networks, customized neural networks, efficient programming of neural networks, etc) Platform: |
Size: 54128640 |
Author:caravan |
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Description: 利用原算法adaboost弱学习器基于决策树桩的方法对样本数据进行多分类(Multi-classification of sample data based on decision tree stump using AdaBoost weak learner) Platform: |
Size: 18432 |
Author:魏小秋 |
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Search - svm decision tree