Description: : 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.
- [NaiveBayes.Rar] - process called CM = Confusion_matrix (tr
- [visualcBayesian1] - bayesian classification of the tradition
- [shifunction] - Pattern Recognition Pattern Recognition-
- [beyes] - 1. Based on the Bayes classification of
- [Classifier4J-0.6-dist] - Classifier4J is a very good java-based c
- [LRP] - Mainly include: logistics and distributi
- [imputation] - Analysis of incomplete datasets: Estimat
- [weight_centre] - Through the center of gravity method to
- [Bayes_Classify] - Bayesian classifier, the use of posterio
- [3] - Bayesian Gaussian image of the value of
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K-meansNB.pdf
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