PREDICTION OF TELECOM SERVICES CONSUMERS CHURN BY USING MACHINE LEARNING ALGORITHMS
Machine learning, or as it is also called automated learning, is a special subfield of scientific information technologies. The name "machine learning" refers to the automated detection of meaningful patterns in large data sets. Machine learning is gaining importance in many different ar...
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| Format: | Article |
| Language: | English |
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Faculty of Economics, University of Tuzla
2022-11-01
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| Series: | Economic Review |
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| Online Access: | http://er.ef.untz.ba/index.php/er/article/view/41 |
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| author | Edin Osmanbegović Anel Džinić Mirza Suljić |
| author_facet | Edin Osmanbegović Anel Džinić Mirza Suljić |
| author_sort | Edin Osmanbegović |
| collection | DOAJ |
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Machine learning, or as it is also called automated learning, is a special subfield of scientific information technologies. The name "machine learning" refers to the automated detection of meaningful patterns in large data sets. Machine learning is gaining importance in many different areas of the economy. One of those areas is the prediction and prevention of consumer churn. There are two basic types of consumer churn, complete churn and partial churn. Machine learning is used to determine the most significant characteristics that play a role in the churn/retention of consumers, and with the help of machine learning it is possible to establish the probability of churn for each individual consumer. Some of the most commonly used machine learning algorithms for this issue are Logistic Regression, Gaussian Naive Bayes, Bernoulli Naive Bayes, Decision Tree, and Random Forest.
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| format | Article |
| id | doaj-art-6c98f058f4274d3fb2b84ae99e247846 |
| institution | Kabale University |
| issn | 1512-8962 2303-680X |
| language | English |
| publishDate | 2022-11-01 |
| publisher | Faculty of Economics, University of Tuzla |
| record_format | Article |
| series | Economic Review |
| spelling | doaj-art-6c98f058f4274d3fb2b84ae99e2478462025-02-10T00:30:46ZengFaculty of Economics, University of TuzlaEconomic Review1512-89622303-680X2022-11-01202PREDICTION OF TELECOM SERVICES CONSUMERS CHURN BY USING MACHINE LEARNING ALGORITHMSEdin Osmanbegović0Anel Džinić1Mirza SuljićUniversity of Tuzla, Faculty of Economics, Bosnia and HerzegovinaCaDa Solucije doo, Bosnia and Herzegovina Machine learning, or as it is also called automated learning, is a special subfield of scientific information technologies. The name "machine learning" refers to the automated detection of meaningful patterns in large data sets. Machine learning is gaining importance in many different areas of the economy. One of those areas is the prediction and prevention of consumer churn. There are two basic types of consumer churn, complete churn and partial churn. Machine learning is used to determine the most significant characteristics that play a role in the churn/retention of consumers, and with the help of machine learning it is possible to establish the probability of churn for each individual consumer. Some of the most commonly used machine learning algorithms for this issue are Logistic Regression, Gaussian Naive Bayes, Bernoulli Naive Bayes, Decision Tree, and Random Forest. http://er.ef.untz.ba/index.php/er/article/view/41machine learningcustomer churncustomer retention |
| spellingShingle | Edin Osmanbegović Anel Džinić Mirza Suljić PREDICTION OF TELECOM SERVICES CONSUMERS CHURN BY USING MACHINE LEARNING ALGORITHMS Economic Review machine learning customer churn customer retention |
| title | PREDICTION OF TELECOM SERVICES CONSUMERS CHURN BY USING MACHINE LEARNING ALGORITHMS |
| title_full | PREDICTION OF TELECOM SERVICES CONSUMERS CHURN BY USING MACHINE LEARNING ALGORITHMS |
| title_fullStr | PREDICTION OF TELECOM SERVICES CONSUMERS CHURN BY USING MACHINE LEARNING ALGORITHMS |
| title_full_unstemmed | PREDICTION OF TELECOM SERVICES CONSUMERS CHURN BY USING MACHINE LEARNING ALGORITHMS |
| title_short | PREDICTION OF TELECOM SERVICES CONSUMERS CHURN BY USING MACHINE LEARNING ALGORITHMS |
| title_sort | prediction of telecom services consumers churn by using machine learning algorithms |
| topic | machine learning customer churn customer retention |
| url | http://er.ef.untz.ba/index.php/er/article/view/41 |
| work_keys_str_mv | AT edinosmanbegovic predictionoftelecomservicesconsumerschurnbyusingmachinelearningalgorithms AT aneldzinic predictionoftelecomservicesconsumerschurnbyusingmachinelearningalgorithms AT mirzasuljic predictionoftelecomservicesconsumerschurnbyusingmachinelearningalgorithms |