Proceedings Article10.1109/ITNEC.2017.8284867
Naive Bayesian algorithm classification model with local attribute weighted based on KNN
Mao Xin,Gang Zhao,Ruoying Sun +2 more
- 01 Dec 2017
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TL;DR: A new Naive Bayesian algorithm classification model with local attribute weighting based on K-nearest neighbor algorithm with high accuracy in the bus line selection prediction is proposed.
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Abstract: In order to better optimize and configure public transport resources, we will find the rules of the bus lines different people taking, and predict which bus lines different people choosing To solve this problem, this paper proposed a new Naive Bayesian algorithm classification model with local attribute weighting based on K-nearest neighbor algorithm In the process of algorithm calculated, we used the K-nearest neighbor algorithm to find the K neighbors to be classified, then calculated the probability of each attribute in K neighbors as the weight of the attribute Later, we put the weight of attribute into Naive Bayesian classification process, which makes the classification model more realistic and predicted the label We used K-nearest neighbor, decision tree and Gaussian naive Bayesian algorithm as control group Experiments were carried out on bus historical data in one city The results show that the model has high accuracy in the bus line selection prediction
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Speeding up incremental wrapper feature subset selection with Naive Bayes classifier
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Attribute weighted Naive Bayes classifier using a local optimization
TL;DR: This paper proposes a novel attribute weighted Naive Bayes classifier by considering weights to the conditional probabilities and reports the results of numerical experiments on several real-world data sets in binary classification, which show the efficiency of the proposed method.
Artificial immune system for attribute weighted Naive Bayes classification
Jia Wu,Zhihua Cai,Sanyou Zeng,Xingquan Zhu +3 more
- 01 Aug 2013
TL;DR: A new Artificial Immune System based Weighted Naive Bayes (AISWNB) classifier is proposed that outperforms other state-of-the-art attribute weighted NB algorithms.
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Attribute weighted Naive Bayes for remote sensing image classification based on cuckoo search algorithm
Yang Juan,Zhiwei Ye,Zhang Xu,Wei Liu,Huazhong Jin +4 more
- 01 Dec 2017
TL;DR: Experimental results demonstrate that the proposed remote image classification approach, the attribute weight of which is learnt through cuckoo search algorithm, has higher classification accuracy and more stable performance.
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