Search - naive bayes classifier algorithm

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[AI-NN-PR] waff-2007-01-11 DL : 0: 一个由Mike Gashler完成的机器学习方面的includes neural net, naive bayesian classifier, decision tree, KNN, a genetic algorithm, and some manifold learning algorithms. -by Mike Gashler a complete machine learning includes the neur al net, naive bayesian classifier. decision tree, KNN, a genetic algorithm, manifold and some learning algorithms.
Date : 2026-01-03 Size : 1.55mb User : lyb
[AI-NN-PR] NaiveBayes DL : 0: 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
Date : 2026-01-03 Size : 159kb User : guifeng2002
[AI-NN-PR] BayesClassifier DL : 0: 贝叶斯分类算法，构造朴素贝叶斯分类器，对给定的中文文本进行分类-Bayesian classification algorithm, Naive Bayes classifier structure of a given Chinese text classification
Date : 2026-01-03 Size : 2kb User : 娜娜
[AI-NN-PR] K-meansNB DL : 0: ：将K—means算法引入到朴素贝叶斯分类研究中，提出一种基于K—means的朴素贝叶斯分类算法。首先用K— me．arks算法对原始数据集中的完整数据子集进行聚类，计算缺失数据子集中的每条记录与个簇重心之间的相似度，把记录赋给距离最近的一个簇，并用该簇相应的属性均值来填充记录的缺失值，然后用朴素贝叶斯分类算法对处理后的数据集进行分类。实验结果表明，与朴素贝叶斯相比，基于K—means思想的朴素贝叶斯算法具有较高的分类准确率。-: K-means algorithm will be introduced to the Naive Bayesian Classifier study, a K-means based on the Naive Bayesian classification algorithm. First of all, with K-me. arks algorithm focus on the raw data of the complete data subset of the cluster, the calculation of missing data for each subset of records and the similarity between the cluster center of gravity to the nearest record assigned to a cluster, and the corresponding attributes of the cluster means to fill the missing value record, and then use Naive Bayes classification algorithm to deal with the data set after classification. The experimental results show that compared with the Naive Bayes, K-means based on the thinking of Naive Bayes algorithm has higher classification accuracy.
Date : 2026-01-03 Size : 169kb User : 李浩
[AI-NN-PR] Games DL : 0: Bayes分类器——算法设计 1．使用决策树(Decision tree)分类算法、朴素贝叶斯（Naï ve Bayes）算法或者K-近邻（kNN）算法（三者任选其一）对给定的训练数据集构造分类器，并在测试数据集上进行分类预测。 2．数据集描述： Tic-tac-toe游戏的二叉分类。Tic-tac-toe游戏示例如下-Bayes classifier- Algorithm 1. Using the decision tree (Decision tree) classification algorithm, Naive Bayes (Naï ve Bayes) algorithm or K-nearest neighbor (kNN) algorithm (choose any one of three) on a given set of training data classification structure, and the test data Classification and Prediction on the set. 2. Data set description: Tic-tac-toe game binary classification. Tic-tac-toe game example is as follows
Date : 2026-01-03 Size : 1.37mb User : vera
[AI-NN-PR] naiveBayesClassify DL : 0: 机器学习算法，朴素贝叶斯分类器，常用作文本分类，或者用在本体匹配算法中用作相似度的计算-Machine learning algorithm, naive bayes classifier, commonly used ZuoWenBen classification, or use in ontology matching algorithm used in the calculation of similarity degree
Date : 2026-01-03 Size : 7kb User : 兰明明