| Naslov: | Comparative analysis of machine learning models for telecommunications churn prediction |
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| Avtorji: | ID Cerjan, Maja (Avtor)
ID Mršić, Leo (Avtor)
ID Rabuzin, Kornelije (Avtor)
ID Boshkoska, Biljana Mileva (Avtor) |
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| Datoteke: |  RAZ_Cerjan_Maja_2025.pdf (12,52 MB)
MD5: 2EBEEB33F12E23AE224DC803CB606675
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| Jezik: | Angleški jezik |
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| Vrsta gradiva: | Neznano |
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| Tipologija: | 1.08 - Objavljeni znanstveni prispevek na konferenci |
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| Organizacija: | FIŠ - Fakulteta za informacijske študije v Novem mestu
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| Opis: | Customer retention is a major problem in the telecommunications industry. This study develops and evaluates models to identify possible churners. Machine learning techniques (“Decision Trees”, “Random Forests”, “Logistic Regression” and “Neural Networks (multilayer perceptron MLP)”) were applied through Python and R to analyze the “Telco Customer Churn” Kaggle dataset, based on customer assests and service usage. The data pre-processing compiled missing data and then standardized it. Evaluation used nested 10-fold cross-validation with an inner loop for hyperparameter tuning and mutual-information top-K feature pruning, with pre-processing confined to training folds. In Python, RF and LR achieve F1(~0.629), with Logistic Regression accuracy ~0.75. In R, Logistic Regression performed best (F1 ≈ 0.60 ± 0.03, Accuracy ≈ 0.80 ± 0.01). Metrics derived from pooled confusion matrices averaged over folds equal outer-fold means, confirming generalization across folds and between Python and R. Research offers empirical evidence for transferring and testing churn prediction models across Python and R in telecommunications analytics, with fully reproducible evaluation and results. |
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| Ključne besede: | customer churn, telecommunications, churn prediction, logistic regression, neural networks (MLP), Python, R, nested cross-validation |
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| Status publikacije: | Objavljeno |
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| Verzija publikacije: | Objavljena publikacija |
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| Leto izida: | 2025 |
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| Št. strani: | Str. [133-146] |
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| PID: | 20.500.12556/ReVIS-13034  |
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| UDK: | 004.85:654 |
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| COBISS.SI-ID: | 265024515 |
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| Opomba: | Nasl. z nasl. zaslona;
Opis vira z dne 16. 1. 2026;
Soavtorji: Leo Mršić, Kornelije Rabuzin, Biljana Mileva Boshkoska;
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| Datum objave v ReVIS: | 22.01.2026 |
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| Število ogledov: | 112 |
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| Število prenosov: | 1 |
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| Metapodatki: |    |
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