Random Forest achieves 99.9% accuracy, precision, recall and F1-score for fraud detection on a 101k-record telecom CDR dataset after Min-Max scaling and SMOTE.
Research on Data Preprocessing and Categorization Technique for Smartphone Review Analysis,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.NI 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
An Efficient Machine Learning-based Framework for Detection and Prevention of Frauds in Telecom Networks
Random Forest achieves 99.9% accuracy, precision, recall and F1-score for fraud detection on a 101k-record telecom CDR dataset after Min-Max scaling and SMOTE.