Description: 用matlab实现的朴素贝叶斯分类源代码，希望对大家有些帮助-Using matlab realize the Naive Bayesian Classifier source code, in the hope that some U.S. help Platform: |
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Author:fanny |
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Description: 贝叶斯算法是基于贝叶斯定理 P(H|X) = P(X|H)P(H) / P(X).。对于多属性的数据集，计算 P(X|Ci) 的开销非常大，为减低计算复杂度，我们做条件独立的假设，即给定元组的类标号，假定属性值有条件地相互独立，即在属性间不存在依赖关系。此程序仅为算法的一个实现，根据训练数据训练分类器-Bayesian algorithm is based on the Bayes theorem P (H | X) = P (X | H) P (H)/P (X).. For multi-attribute data sets, computing P (X | Ci) of the overhead is very large, in order to reduce the computational complexity, we do conditional independence assumption that a given tuple class label, it is assumed that property values conditionally independent of each other, that does not exist in the inter-attribute dependencies. This procedure is only an implementation of algorithm, according to training data classifier training Platform: |
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Author:guifeng2002 |
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Description: 朴素贝叶斯算法，以函数形式实现，花了一个上午的时间-Naive Bayes algorithm, in order to function the form of implementation, a morning flower time Platform: |
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Author:张其 |
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Description: 《机器学习》课上的作业，PCA和LDA降维，尽管网上很多，但很少注释，另外细节上也没注意。这里有很详细的注释。另外还附上一个Naive贝叶斯分类器，大家可以作比较。附带的图像包是OLR人脸。ReducedDim为想要提取的特征数，不是百分比！-" Machine learning" classes on the homework, PCA and LDA dimensionality reduction, even though a lot of online, but few notes, on the other did not pay attention to details. Here there is a very detailed notes. In addition, attach a Naive Bayesian classifier, we can compare. Fringe image packages are OLR people face. ReducedDim you want to extract the characteristics of a few, not a percentage! Platform: |
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Author: |
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Description: 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 famous classifiers in machine learning. They are 1) PCA, 2) LDA and 3) Naive Bayesian. The detail theory behind these classifier can be found text book <<Introduction to Machine Learning>>. Besides the implementation of these 3 algorithms, the main.m for testing and a brief testing report is also included. (The testing is on data set acoustic_train_data) Enjoy:) Platform: |
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Author:hhj |
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Description: 本报告对 朴素贝叶斯模型及线性判别分析、二次判别分析 进行系统测试
“生成模型”是机器学习中监督学习方法的一类。与“判别模型”学习决
策函数和条件概率不同，生成模型主要学习的是联合概率分布??(??,??)。本
文中，我们从朴素贝叶斯算法入手，分析比较了几种常见的生成模型（包
括线性判别分析和二次判别分析）应用于多因子选股的异同，希望对本领
域的投资者产生有实用意义的参考价值。(This report gives a systematic test of naive Bayesian model, linear discriminant analysis and two discriminant analysis
"Generation model" is a kind of supervised learning method in machine learning. Learning from "discriminant model"
The strategy function and the conditional probability are different. The generation model mainly studies the joint probability distribution. book
In this paper, we analyze and compare several common generation models (packages) from the naive Bayes algorithm.
The linear discriminant analysis and the two discriminant analysis are applied to the similarities and differences of multi factor stock selection.
The investors of the domain have a useful reference value.) Platform: |
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Author:隔壁的头老李 |
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