Hybrid Data Mining Method of Telecom Customer Based on Improved Kmeans and XGBoost

Shi, Yongge; Yan, Shaoyun; He, Meibin; Li, Xiangjun

doi:10.1088/1742-6596/2010/1/012060

Cited by 4 publications

(3 citation statements)

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“…First is the Manhattan cluster distance which is the distance between two points. And it is also called urban block distance [1,3]:…”

Section: K-means Algorithmmentioning

confidence: 99%

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Explore the role and emphasis of K-Means, Decision Tree and Distance Based algorithms in data exception detection

Chen

2023

J. Phys.: Conf. Ser.

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K-Means, Decision Tree and Distance-Based algorithms are 3 important ways of classifying data. These three algorithms have different methods and focus on data classification. Therefore, they are always applied into different scenarios. K-Means algorithm is to divide three-dimensional data or two-dimensional data into several clusters to facilitate subsequent data processing and analysis. Decision Tree is based on the “tree” structure to make decisions. It is an important classification and regression method in data mining technology. It is a prediction analysis model expressed in the form of tree structure (including binary tree and multi tree). When it comes to the Distance-Based algorithm, it is a common anomaly detection method applicable to various data domains. It defines outliers based on the nearest neighbor distance. The purpose of this paper is to explore the kernel of three anomaly detection algorithms through an example of data anomaly detection. Therefore, in this paper, all three algorithms’ commonalities and differences will be discussed and illustrated through a case of data exception handling.

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“…First is the Manhattan cluster distance which is the distance between two points. And it is also called urban block distance [1,3]:…”

Section: K-means Algorithmmentioning

confidence: 99%

“…K-Means technique clusters data into numerous distinct subsets. Clustering can be employed alone to determine the data's internal distribution structure or as a forward process for classification [1][2][3]. Therefore, K-Means algorithm is often used to solve resource allocation problems.…”

Section: Introductionmentioning

confidence: 99%

Explore the role and emphasis of K-Means, Decision Tree and Distance Based algorithms in data exception detection

Chen

2023

J. Phys.: Conf. Ser.

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“…Zhong Jun et al proposed a hybrid algorithm of convolutional auto-encoding and Gaussian mixture, which was applied to the feature extraction of ECG signals, and saved a lot of time and effort of manual labeling [8]. Shi Yongge et al proposed a hybrid algorithm of Kmeans and Extreme Gradient Boosting (XGBoost) to mine designated telecom customers with special behaviors from the vast voice communication records of telecom companies [9]. In view of the shortcomings of the Kmeans and DBSCAN algorithms and the hybrid algorithm idea proposed by the above scholars, this paper proposes an improved algorithm of DBSCAN combined with the Kmeans algorithm.…”

Section: Related Workmentioning

confidence: 99%

Analysis of influencing factors on excellent teachers' professional growth based on DB-Kmeans method

Gao

Ding

Han

et al. 2022

EURASIP J. Adv. Signal Process.

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The Kmeans clustering algorithm is widely used for the advantages of simplicity and efficient operation. However, the lack of clustering centers in the algorithm usually causes incorrect category of some discrete points. Therefore, in order to obtain more accurate clustering results when studying the factors affecting the professional growth of outstanding teachers, this paper proposes an improved algorithm of Kmeans combined with DBSCAN. Observing the clustering results of the influencing factors and calculating the evaluation standard values of the clustering results, it is found that the optimized DB-Kmeans algorithm has obvious improvements in the accuracy of the clustering results, and the clustering effect of the algorithm on edge points is more advantageous than the original algorithms according to the scatter diagram.

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Improved Kmeans Algorithm Based on Privacy Protection

Wang

Yang

2023

Machine Learning for Cyber Security

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Hybrid Data Mining Method of Telecom Customer Based on Improved Kmeans and XGBoost

Cited by 4 publications

References 0 publications

Explore the role and emphasis of K-Means, Decision Tree and Distance Based algorithms in data exception detection

Explore the role and emphasis of K-Means, Decision Tree and Distance Based algorithms in data exception detection

Analysis of influencing factors on excellent teachers' professional growth based on DB-Kmeans method

Improved Kmeans Algorithm Based on Privacy Protection

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