Description: 基于GMM的概率神经网络PNN具有良好的泛化能力，快速的学习能力，易于在线更新,并具有统计学的贝叶斯估计理论基础，已成为一种解决像说话人识别、文字识别、医疗图像识别、卫星云图识别等许多实际困难分类问题的很有效的工具。而且PNN不但具有GMM的大部分优点，还具有许多GMM没有的优点，如强鲁棒性，需要更少的训练语料，可以和其他网络其他理论无缝整合等。-GMM based probabilistic neural network PNN good generalization ability, the ability to learn fast, easy online updates, and with the Bayesian statistical theory based on estimates, and has become a solution as speaker recognition, text recognition, medical image recognition, satellite images and other real recognition when difficulties classification of very effective tool. But GMM PNN is not only the most advantages, but also has many advantages GMM not as strong robustness, require less training corpus, and other networks to other theories, such as seamless integration. Platform: |
Size: 7158 |
Author:姜正茂 |
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Description: 基于GMM的概率神经网络PNN具有良好的泛化能力，快速的学习能力，易于在线更新,并具有统计学的贝叶斯估计理论基础，已成为一种解决像说话人识别、文字识别、医疗图像识别、卫星云图识别等许多实际困难分类问题的很有效的工具。而且PNN不但具有GMM的大部分优点，还具有许多GMM没有的优点，如强鲁棒性，需要更少的训练语料，可以和其他网络其他理论无缝整合等。-GMM based probabilistic neural network PNN good generalization ability, the ability to learn fast, easy online updates, and with the Bayesian statistical theory based on estimates, and has become a solution as speaker recognition, text recognition, medical image recognition, satellite images and other real recognition when difficulties classification of very effective tool. But GMM PNN is not only the most advantages, but also has many advantages GMM not as strong robustness, require less training corpus, and other networks to other theories, such as seamless integration. Platform: |
Size: 7168 |
Author:姜正茂 |
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Description: 图像分类器，可实现贝叶斯滤波以及分类，应用与人脸识别，车牌识别等等。-Image classifier, Bayesian filtering can be achieved as well as the classification, application and face recognition, license plate recognition and so on. Platform: |
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Author: |
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Description: 图像的贝叶斯分类，将模式识别方法与图像处理技术相结合，掌握利用最小错分概率贝叶斯分类器进行图像分类的基本方法-Bayesian image classification, the pattern recognition method and image processing technology, to master the use of the smallest misclassification probability of Bayes classifier for image classification of basic methods Platform: |
Size: 1024 |
Author:孟星 |
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Description: naive bayes方法是用于分类的一个传统方法，它是产生的比较早的一个方法，分类的准确度比较高。-naive bayes method is used for the classification of a traditional method, which is generated as early as one way of comparison, classification accuracy is relatively high. Platform: |
Size: 1024 |
Author:李萍 |
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Description: 基于贝叶斯最小错误率算法的崇明岛遥感图像分类程序。并且有饼状图显示各类地物比例-Minimum error rate based on Bayesian algorithm for Chongming Island, the remote sensing image classification procedures. And the pie chart below shows the proportion of various types of features Platform: |
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Author:李琛 |
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Description: 实现基本的朴素贝叶斯分类算法，用以将图片按照一定要求分类-To achieve the basic Naive Bayesian classification algorithm for the image classification in accordance with certain requirements Platform: |
Size: 189440 |
Author:Edward Lee |
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Description: Bayesian classification algorithm based on image threshold segmentation iterative threshold segmentation algorithm for the best environment to run correctly matlab7.0 Platform: |
Size: 4096 |
Author:nounou28 |
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Description: 分类是数据挖掘 、机器学习 和模式识别 中一个重要的研究领域。分类的目的是学会一个分类模型 (称作分类器)，该模型能把未知类别的数据项映射到给定类别中。目前发展较成熟的几种分类算法 如决策树、神经网络、贝叶斯方法、遗传算法等。分类具有广泛的应用，例如医学诊断、信用卡系统的信用分级、图像模式识别等。本毕业设计通过使用鸢尾属植物(IRIS)数据集，对当前数据挖掘中具有代表性的优秀分类算法进行分析和比较，总结出了各种算法的特性，为使用者选择算法或研究者改进算法提供了依据。-Classification of data mining, machine learning and pattern recognition is an important area of research. The purpose of classification is to learn a classification model (called classifier), the model can unknown types of data items mapped to a given category. Currently the more mature types of classification algorithms such as decision trees, neural networks, Bayesian methods, genetic algorithms. Classification with a wide range of applications such as medical diagnosis, credit card system, credit rating, image pattern recognition. The graduation project by using the Iris genus (IRIS) data sets, data mining has on the current outstanding representative of the analysis and comparison of classification algorithms, summed up the characteristics of various algorithms for researchers to improve the user selection algorithm or algorithm provided.
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Author:江霞 |
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Description: 类的目的就是根据现有的图像特征建立一个分类器，能够对未知的图像类型进行预测。在现有众多分类
算法中，贝叶斯分类器由于其坚实的数学理论基础并能综合先验信息和数据样本信息，成为"-3前机器学习和数据挖
掘的研究热点之一。本文论述了内容图像检索中基于贝叶斯分类器的图像分类技术。介绍了贝叶斯分类器，叙述了
利用贝叶斯分类器进行图像分类的方法，以及图像特征的分布假定。最后通过对分类器的探讨，总结了贝叶斯估计
分类的不足。-The purpose of class is based on an existing image features to create a classifier able to predict the unknown image type. Many of the existing classification algorithm, the Bayesian classifier because of its solid mathematical theory-based and comprehensive information prior information and data samples, a " -3 before the machine learning and data mining research focus of this paper discusses the Content-based Image Retrieval Bayesian classifier image classification techniques. introduced Bayesian classifier, described the use of Bayesian classifier for image classification methods, and the distribution of image features is assumed finally by classifier discussion summarizes the classification of the lack of Bayesian estimation. Platform: |
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Author:刘东 |
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Description: 最小错误概率贝叶斯分类器的matlab程序，可用于二维数据的分类以及分类效果的图像显示，可帮助初学者加深对贝叶斯分类算法的理解。-This is a matlab program of the minimum probability of error of Bayesian classifier.Which can display the image of two-dimensional data classification and the classification results . It can help beginners to deepen the understanding of Bayesian classification algorithm .
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Size: 2048 |
Author:chenxiao |
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