Locally weighted na?ve Bayes classifier is such a classifier that encompasses the power of NB and k-NN algorithms. In this work, we have implemented a self-labeled weighted variant of local learner which uses NB as the base classifier of self-training scheme. We performed an in depth ...
Application of Naive Bayes in Document Classification 来自 知网 喜欢 0 阅读量: 14 摘要: Na ve Bayesian theory is a classic technology of machine learning,and is applied in document classification.The process of sample training and classifying calculation was presented,and a document classifier was...
Naive Bayes classifier For a NB classification problem we should learn: 1. P(X1,...Xn|C)=Πni=1P(Xi|C)P(X1,...Xn|C)=Πi=1nP(Xi|C), for each class assumes that XiXi and XjXj are conditionally independent of each other given C. 2. P(C) To classify: given xx, choose c th...
The Naive Bayes (NB) classifier is a powerful supervised algorithm widely used in Machine Learning (ML). However, its effectiveness relies on a strict assumption of conditional independence, which is often violated in real-world scenarios. To address this limitation, various studies have explored ex...
在《机器学习 朴素贝叶斯分类器(Machine Learning Naive Bayes Classifier)》一文中,我们介绍了朴素贝叶斯分类器的原理。现在,让我们来实践一下。 在这里,我们使用一份皮马印第安女性的医学数据,用来预测其是否会得糖尿病。文件一共有768个样本,我们先剔除缺失值,然
We introduce the notion of naive evidential classifier. This classifier, which has a structure mirroring the naive Bayes classifier, is based on the Transferable Belief Model and uses mass assignments as its uncertainty model. This new method achieves more robust inferences, mainly by explicitly model...
The experimental results show that the proposed Naive Bayes classifier model has good performance for different SNS media, and a semi-supervised learning effectively works for the data consisting of long comments. In addition, the proposed method is applied to detect flaming incidents, and we show ...
Longwall top coal caving technology is one of the main methods of thick coal seam mining in China, and the classification evaluation of top coal cavability in longwall top coal caving working face is of great significance for improving coal recovery. However, the empirical or numerical simulation...
we have used ten RQA parameters to quantify the important features in the EEG signals.These features were fed to seven different classifiers: Support vector machine (SVM), Gaussian Mixture Model (GMM), Fuzzy Sugeno Classifier, K-Nearest Neighbor (KNN), Naive Bayes Classifier (NBC), Decision Tre...
In this work we introduce a new distance estimation technique by boosting and we apply it to the K-Nearest Neighbor Classifier (K-NN). Instead of applying AdaBoost to a typical classification problem, we use it for learning a distance function and the resulting distance is used into K-NN....