Customer Churn Prediction in the Mobile Telecommunication Industry Using Decision Tree Classification Algorithm

Manjupriya, R.; Poornima, A

doi:10.1166/jctn.2018.7540

Cited by 4 publications

(2 citation statements)

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“…An important part of decision tree classification algorithms is to find the best features to share. By subdividing the rights of development modules, a decision tree that can distinguish training programs is finally found [15]. e attribute selection metric is a splitting strategy primarily.…”

Section: Decision Tree Classificationmentioning

confidence: 99%

Training Method of Flute Breath Based on Big Data of Internet of Things

Sun

2022

Scientific Programming

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As a traditional musical instrument, the flute has a long history and is loved by people. The flute has a wider range, and its timbre has strong penetrating and expressive power. This is not only a unique solo instrument but also occupies an important position in the symphony orchestra. Breath training on the flute is an essential step in flute learning. However, in the traditional flute breath training process, teachers cannot observe the students’ practice in real time, and the training process is relatively simple, resulting in the final training effect not being obvious and the students’ breath stability not being significantly improved. In order to solve this problem, this paper applied the Internet of Things (IoT) big data technology to the flute breath training process. The flute breath training system based on big data of Internet of Things was used to conduct professional breath training for students. Through the tests of the trained students, it was found that the training method of flute breath using the big data of the Internet of Things improved the students’ leg strength and chest, abdomen, and back strength. In the long-tone practice, the students’ exhalation time increased by 1.472 seconds, and the students’ breath stability increased by 7.1%, which laid a good foundation for the students to learn the flute in the future.

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Section: Decision Tree Classificationmentioning

confidence: 99%

Training Method of Flute Breath Based on Big Data of Internet of Things

Sun

2022

Scientific Programming

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“…The complexity of the predictive models varies based on the used machine learning algorithms. For example, Decision Tree algorithm applied by (Manjupriya and Poornima 2018) While there are several approaches to analyzing customer behaviour in different aspects, we could not find an approach using a combination of different data sources to construct the customer profile. The disadvantage of models relying on one source of data is the limited usage of these models.…”

Section: Motivationmentioning

confidence: 99%

Graph-based Knowledge Modeling and Analytics for Capturing and Predicting Customer Behaviour

Zahran¹

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Understanding customer behaviour is a challenging problem. While the customer produces a large amount of data with each touch point, most of the proposed models focus on one data source in their predictive analysis approaches. This research proposes a customer profile model based on 360 customer view. To this end, we first model a simplified data model and the basic entities based on the existing models. Then, we perform extensive feature engineering techniques, including extracting new features and transforming features to enhance their behaviour in the predictive model. Through the experimentations, we show that the models based on graphs achieve good performance. To this end, we propose a graph-based neural network capable of multitasking without sacrificing the task's performance. We examine three tasks to predict customer intentions. The final results reveal that the set of features with customer information from different data sources positively influences the predictive algorithms' performance.

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Decision Tree Classification Algorithm in College PE Teachers’ Score Analysis

Sun

2020

Advances in Intelligent Systems and Computing

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Customer Churn Prediction in the Mobile Telecommunication Industry Using Decision Tree Classification Algorithm

Cited by 4 publications

References 0 publications

Training Method of Flute Breath Based on Big Data of Internet of Things

Training Method of Flute Breath Based on Big Data of Internet of Things

Graph-based Knowledge Modeling and Analytics for Capturing and Predicting Customer Behaviour

Decision Tree Classification Algorithm in College PE Teachers’ Score Analysis

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