4 results for “topic:mobilepriceclassification”
Mobile Price Range Prediction: Use sales data to build a classification model for mobile phone price ranges. Features include battery power, camera, memory, and connectivity. Split data, apply logistic regression, KNN, SVM (linear and rbf), and evaluate using confusion matrices. Select the most accurate model.
Mobile price classification using SVM with hyperparameter tuning and feature selection technique. Accuracy is 95%.
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📱 Classify mobile prices accurately using SVM based on specs like RAM and Battery, ensuring reliable insights for device buyers.