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Description: active support vector machine
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Size: 108544 |
Author: 江维 |
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Description: 机器学习是人工智能的一个子领域，是人工智能中非常活跃且范围甚广的主要核心研究领域之一，也是现代智能系统的关键环节和瓶颈。机器学习吸取了人工智能、概率统计、计算复杂性理论、控制论、信息论、哲学、生理学、神经生物学等学科的成果，主要关注于开发一些让计算机可以自动学习的技术，并通过经验提高系统自身的性能。本文介绍了机器学习的概念、基本结构和发展，以及各种机器学习方法，包括机械学习、归纳学习、类比学习、解释学习、基于神经网络的学习以及知识发现等，并简单叙述了机器学习的相关算法，包括决策树算法、随机森林算法、人工神经网络算法、SVM算法、Boosting与Bagging算法、关联规则算法、贝叶斯学习算法以及EM算法等，最后还指出了机器学习的应用及其发展趋势。-Machine learning is a subset of the field of Artificial Intelligence,is very active in Artificial Intelligence and a wide range of research in the field of one of the main core, is the key and the bottleneck of a modern intelligent system.Machine Learning has absorbed the results of Artificial Intelligence, Probability and Statistics, Computational Complexity Theory, Cybernetics, Information Theory, Philosophy, Physiology and Neurobiology, and other disciplines.It concerns mainly about how to develop some of technology which can make the computer auto-learning,and through experiences to improve the performance of the system itself.This paper introduces the concept,the basic structure and development of machine learning, and a variety of machine learning methods,including machine learning, inductive learning, learning by analogy, explanation-based learning,based on neural network learning and knowledge discovery, and so on. And briefly descrip the algorithms of machine learning,includin
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Size: 32768 |
Author: lzl |
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Description: 使用核PcA来识别图片，图片为200张测试图片，200张训练图片，包含在在压缩文件中。-To identify the use of nuclear PcA picture, pictures, for 200 test images, 200 training images, is included in the compressed file.
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Size: 3163136 |
Author: 戴步成 |
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Description: SVM classification
This routine classify the training set with a support vector machine using quadratic programming algorithm (active constraints method)
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Size: 399360 |
Author: pavl |
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Description: 交互支持向量机学习算法能解决一些监督学习问
题中学习样本较少的问题, 它以支持向量机(SVM ) 方法为
基础, 将设计分类器变成一个交互的过程, 即: 根据对已知
样本进行的SVM 分类器设计, 主动采样选择“有用”的新样
本, 并进行下一步SVM 分类器的设计。与普通SVM 法相
比, 该方法所需的样本量大大降低, 而且可能达到更好的推
广能力。文本信息过滤问题的实例说明了该算法的有效性。-Interactive support vector machine learning algorithm for supervised learning problems could solve some small problems in the study sample, it is to support vector machine (SVM) method based classifier will be designed into an interactive process, namely: 根据 for known samples for the SVM classifier design, active sampling select " useful" in the new sample, and the next step SVM classifier design. Compared with the general SVM, the method of sample required is greatly reduced, and may achieve better generalization ability. Text information filtering problem given to illustrate the effectiveness of the algorithm.
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Size: 294912 |
Author: 罗朝辉 |
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Description: 支持向量机以统计学习理论作为坚实的理论依据，借助优化方法解决及其学习的一种新工
具.近年来，支持向量机受到人们的广泛关注，在理论研究和算法实现方面都有了很大的突
破，成为现代机器学习的热点课题.-Support vector machine(SVM)is a new approach that can solve machine learning
problem with optimization methods. In recent years,there has been a surge of interest in
SVM.It has achieved a prodigious progress in the theory research and algorithm
implement, thus has been an active research area in machine learning
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Size: 830464 |
Author: ping |
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Description: 遥感图像分类工具箱，包含多种基于支持向量机分类器的主动学习算法-active learning toolbox, used for remote sensing data classification, includes most popular svm-based active learning algorithms.
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Size: 8710144 |
Author: zhouxiong |
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Description: 老外写的直接转矩控制+空间矢量的内置永磁体电机无传感器控制的文章-This paper proposes an implementation of a motion sensorless control system in wide speed range based on “active
flux” observer, and direct torque and flux control with space vector
modulation (DTFC-SVM) for the interior permanent magnet synchronous motor (IPMSM), without signal injection.
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Size: 534528 |
Author: xianggui |
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Description: 提出了基于主动学习SVM的局部放电模式识别方法。将主动学习的思想引用到“一对一”多分类SVM分类器,选用基于后验概率的釆样函数对放电样本进行选择,挑选出对分类器最有价值的样本进行训练。
-Puts forward the partial discharge pattern recognition method based on active learning SVM. Will reference to the one to one the ideology of active study of classification of SVM classifier, sample selection based on the calculation of posterior probability function of discharge samples to choose, pick out the most valuable training samples for classifier
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Size: 8184832 |
Author: 娜娜 |
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Description: This the source code for stomachcancer detection using active contour segmentation and SVM classification method-This is the source code for stomachcancer detection using active contour segmentation and SVM classification method
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Size: 2002944 |
Author: malathimalathi |
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Description: 基于有效磁链的IPMSM点击i无速度传感器控制-Active Flux DTFC-SVM Sensorless Control of IPMSM
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Size: 537600 |
Author: chen |
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