Description: 这个源码提供了如何利用高斯混合模型去做影像辨识的模型分类-the source how to use a Gaussian mixture model to do imaging Identification Classification Model Platform: |
Size: 16058 |
Author:小王 |
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Description: 云分类器，一种基于云模型理论的分类程序。程序中使用云分类器对Iris数据集进行了测试-cloud classifier, a theoretical model based on cloud classification procedure. Procedures used for cloud classification of Iris data set for testing Platform: |
Size: 3072 |
Author:王力 |
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Description: matlab环境下，基于云模型的分类器，包括基于例子群优化的云分类器，和属性相似度云分类器。-Matlab environment, based on cloud model for the classification, including examples Swarm Optimization Based on the cloud classifier, and attribute similarity cloud classifier. Platform: |
Size: 7168 |
Author:王力 |
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Description: This code is to estimate the parameter of model of Mixture Gauss which is popular model used in pattern classification .
JAVA 写的估计复合高斯模型中的参数
-This code is to estimate the parameter of model of Jian Gauss which is popular model used in pattern classification. Java was estimated composite Gaussian model parameters Platform: |
Size: 5120 |
Author:修宇 |
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Description: 这个源码提供了如何利用高斯混合模型去做影像辨识的模型分类-the source how to use a Gaussian mixture model to do imaging Identification Classification Model Platform: |
Size: 15360 |
Author:小王 |
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Description: Libsvm is a simple, easy-to-use, and efficient software for SVM
classification and regression. It can solve C-SVM classification,
nu-SVM classification, one-class-SVM, epsilon-SVM regression, and
nu-SVM regression. It also provides an automatic model selection
tool for C-SVM classification. This document explains the use of
libsvm.
-Libsvm is a simple, easy-to-use, and efficient software for SVM classification and regression. It can solve C-SVM classification, nu-SVM classification, one-class-SVM, epsilon-SVM regression, and nu-SVM regression. It also provides an automatic model selection tool for C-SVM classification. This document explains the use of libsvm. Platform: |
Size: 461824 |
Author:陈中 |
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Description: 搜索引擎的研究与设计.rar The Research and Design of Search Engine
吉 林 大 学
硕 士 学 位 论 文
搜索引擎（Search Engine）是一个对互联网上的信息资源进行搜集整理，
然后供用户查询的系统，它包括信息搜集、信息整理和用户查询三部分，以目
录分类或全文检索的方式来提供查询服务。本文提出了一种简化的向量空间检
索模型，通过统计主题词条对文档的贡献度来建立倒排序索引库，为用户提供
智能的检索服务。-search engine research and design. Rar The Research and Design of Search Engine Jilin University master's degree thesis search engines (Search Engine) the Internet is one of the information resources are collected, then the user query system, which includes information gathering, information received three inquiries and users, directory or full-text retrieval classification approach to provide inquiry services. This paper presents a simplified retrieval of vector space model, through statistical MeSH of the document's contribution to the establishment of the index ranking down to provide users with intelligent retrieval services. Platform: |
Size: 361472 |
Author:八云 |
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Description: 基于类覆盖算法和粒子群优化的神经网络解决模式分类问题-algorithm based on the type coverage and PSO the neural network model to solve classification problems Platform: |
Size: 1370112 |
Author:老农 |
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Description: 隐马尔可夫模型源代码，可用于图像处理，分类，压缩，去噪等等。-Hidden Markov Model source code, can be used for image processing, classification, compression, denoising, etc.. Platform: |
Size: 696320 |
Author:王一笑 |
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Description: H.264的可分级编码标准草案Joint Scalable Video Model 3的标准文档，包含时域，空域，FGS编码。 -H.264 coding standard classification of the draft Joint Scalable Video Model 3 standard documents, including time-domain, airspace, FGS coding. Platform: |
Size: 1271808 |
Author:李金 |
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Description: 一种基于局部密度比权重设置模型的加权支持向量回归模型来单步求解多分类问题：该方法先分别对类样本中每类样本利用局部密度比权重设置模型求出每个样本的权重隶属因子,然后运用加权lib支持向量回归算法对所有样本进行训练,获得回归分类器,希望对大家有用!-Based on local density than the right to re-set model of weighted support vector regression models to single-step to solve multi-classification problems: The method is first on the type of samples, respectively, for each type of samples the use of local density than the right to re-set the model to derive the right of each sample weight attached to factor, and then use lib weighted support vector regression algorithm for all samples for training, access to regression classifier, hope useful for all of us! Platform: |
Size: 41984 |
Author:郭大 |
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Description: libsvm is a simple, easy-to-use, and efficient software for SVM
classification and regression. It solves C-SVM classification, nu-SVM
classification, one-class-SVM, epsilon-SVM regression, and nu-SVM
regression. It also provides an automatic model selection tool for
C-SVM classification. This document explains the use of libsvm.
Platform: |
Size: 295936 |
Author:baolij |
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Description: K-MEANS聚类算法，以及PSO和QPSO算法改进K-MEANS算法，breastcancer数据验证了该分类模型的有效性-K-MEANS clustering algorithm, and the PSO algorithm and QPSO to improve K-MEANS algorithm, breastcancer data verified the validity of the classification model Platform: |
Size: 43008 |
Author:李慧 |
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Description: 在具有模式的完整统计知识条件下，按照贝叶斯决策理论进行设计的一种最优分类器。分类器是对每一个输入模式赋予一个类别名称的软件或硬件装置，而贝叶斯分类器是各种分类器中分类错误概率最小或者在预先给定代价的情况下平均风险最小的分类器。-In a model under the condition of complete statistical knowledge, in accordance with the Bayesian decision theory to design an optimal classifier. Classifier is the input mode of each name given to a category of software or hardware devices, and Bayesian classifier is the classifier in the smallest classification error probability or the cost of pre-given circumstances smallest average risk classifier. Platform: |
Size: 3072 |
Author:御风疾书 |
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Description: 基于weka的分类算法，用于weka拓展应用。朴素贝叶斯模型发源于古典数学理论，有着坚实的数学基础，以及稳定的分类效率。同时，该算法所需估计的参数很少，对缺失数据不太敏感，算法也比较简单。理论上，与其他分类方法相比具有最小的误差率。-Based on the classification algorithm weka, weka develop applications for. Naive Bayes model originated in the classical mathematical theory, has a solid mathematical basis, as well as the stability of the classification efficiency. At the same time, the algorithm estimates the parameters required for small, less sensitive to missing data, the algorithm is also relatively simple. In theory, when compared with other classification methods with the smallest margin of error. Platform: |
Size: 7168 |
Author:zhangrui |
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Description: 实现了 SVM 在医学图像分类中的应用，通过医学图像的实验结果验证了该方法的有效性。
对 SVM 算法进行了深入研究，结合量子行为的粒子群算法的优点，提出了一种量子行为的粒子群算法和 SVM 结合的混合分类模型，应用于医学图像的分类中。
深入研究了 K-means 算法，结合了无监督聚类和监督分类方法的优点，提出了一种 K-means 和 SVM 结合的混合分类模型，并应用于医学图像的分类中。
利用粒子群和量子行为的粒子群算法对 K-means 算法进行了改进，并将改进的K-means 算法与 SVM 算法结合形成全自动分类模型，并且把它应用于医学图像的分类中。
-SVM in the classification of medical image applications, medical images through the experimental results verify the effectiveness of the method. SVM algorithm conducted in-depth research, combined with the quantum behavior of the advantages of particle swarm optimization, PSO and SVM combined behavior of a quantum mixed classification model, applied to medical image classification. In-depth study of the K-means algorithm combines the advantages of unsupervised clustering and supervised classification method, propose a hybrid combination of a K-means and SVM classification model, and applied to the classification of medical images. Improved particle swarm algorithm using particle swarm and quantum behavior of the K-means algorithm, and improved K-means algorithm and SVM algorithm combined with the formation of a fully automatic classification model, and apply it to medical image classification. Platform: |
Size: 1626112 |
Author:招伟杰 |
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Search - Classification Model