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一个很好的文本分类器,采用朴素贝叶斯分类的方法,并加以改进!-a very good text classifiers using Bayesian classification methods, and improved!
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a Java toolkit for training, testing, and applying Bayesian Network Classifiers. Implemented classifiers have been shown to perform well in a variety of artificial intelligence, machine learning, and data mining applications. -a Java toolkit for tra
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图像模式识别
模板匹配法
神经网络分类器
几何分类器
基于概率统计的贝叶斯分类器-image pattern recognition template matching neural network classifiers classification is based on geometric probability and statistics Bayesian classifier
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基于文献《Boosted Bayesian Network Classifiers》的实现代码。
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利用matlab软件对模式识别进行了很好的仿真,利用贝叶斯分类器对男女生进行了很好的分类。-Pattern recognition using matlab software had a very good simulation, the use of Bayesian Classifiers for boys and girls had a very good classification.
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This package contains Matlab m-files for learning finite Gaussian mixtures from sample data and performing data classification with Mahalanobis distance or Bayesian classifiers. Each class in training set is learned individually with one of the three
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Pattern recognition using matlab software had a very good simulation, the use of Bayesian Classifiers for boys and girls had a very good classification.
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贝叶斯网络分类,matlab语言编写的,是一个很不错的算法-Bayesian network classifiers, matlab language, is a very good algorithm
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这是自己写的一个贝叶斯网络分类器,可能存在问题,自己调一下-This is to write a Bayesian network classifiers, there may be problems, make your own look
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贝叶斯分类器的分类原理是通过某对象的先验概率,本文详细介绍贝叶斯分类器,使用贝叶斯分类器对样本进行训练分类,得到良好分类结果,并对分类结果进行分析。-Principle of Bayesian classifiers is through prior probability of an object, the paper describes Bayesian classifier, Bayesian classifier using the training sample classificat
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介绍模式识别的基本概念,详述了贝叶斯,参数估计,线性分类器,神经网络,随机方法,无监督学习与聚类等-Introduce the basic concepts of pattern recognition, Bayesian detailed, parameter estimation, linear classifiers, neural networks, stochastic methods, unsupervised learning and clustering, etc.
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jBNC is a Java toolkit for training, testing, and applying
Bayesian Network Classifiers. Implemented classifiers have been
shown to perform well in a variety of artificial intelligence,
machine learning, and data mining applications.
jBNC
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Bayesian Network Classifiers In Weka
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基于贝叶斯网络的分类器实现,使用C++编写,不错,可以参考-Based on Bayesian network classifiers achieve C++ writing, yes, you can reference
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对五种典型的贝叶斯网分类器进行了分析与比较。在总结各种分类器的基础上,对它们进行了实验比较,讨论了各自的特点,提出了一种针对不同应用对象挑选贝叶斯网分类器的方法。 -Of five kinds of typical bayesian network classifiers are analyzed and compared. On the basis of summarizing the various classifiers, experiments have been carried out
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机器学习领域经典分类算法综述,包括Decision Tree(ID3、C4.5(C5.0)、CART、PUBLIC、SLIQ和SPRINT算法),三种典型贝叶斯分类器(朴素贝叶斯算法、TAN算法、贝叶斯网络分类器),k-近邻 、 基于数据库技术的分类算法( MIND算法、GAC-RDB算法),基于关联规则(CBA:Classification Based on Association Rule)的分类(Apriori算法),支持向量机分类,基于软计算的分类方法(粗糙集(rough set)、遗传
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这是matlab编写的3个常用机器学习分类器代码。其中包括了: 1)PCA 分类其;2)LDA分类器:3)naive贝叶斯分类器。 3个算法的实现参考了《Introduction to Machine
Learning》。 除了这3个分类算法的实现外,代码里面还包含了用于测试的main.m 主程序和一个实验的简要报告。实验在著名数据集acoustic_train_data 上进行。-This source code includes the implementation of three f
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模式识别 北京大学 本科生课程 课件 (包括贝叶斯模型、最近邻、SVM、线性与非线性分类器、boosting、统计学习、非监督学习等)-Pattern Recognition Peking University Courseware (including Bayesian model, the nearest neighbor, SVM, linear and non-linear classifiers, boosting, statistical learning, unsupervised
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分类器的性能比较与调优:
使用scikit-learn 包中的tree,贝叶斯,knn,对数据进行模型训练,尽量了解其原理及运用。
使用不同分析三种分类器在实验中的性能比较,分析它们的特点。
本实验采用的数据集为house与segment。(Performance comparison and optimization of classifiers:
We use tree, Bayesian and KNN in scikit-learnpackage to train the dat
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