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mobilepriceclassification

Here are 3 public repositories matching this topic...

Sai-Likhith / Mobile-Price-Range-Prediction-A-Data-Science-Approach

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.

python data-science machine-learning rbf-kernel logistic-regression svm-classifier knn-classification mobilepriceclassification

Updated Jun 21, 2023
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Khalidur-sujon / Mobile-Price-Classification

Mobile price classification using SVM with hyperparameter tuning and feature selection technique. Accuracy is 95%.

eda feature-selection svm-model hyperparameter-tuning mutual-information svm-classifier mobilepriceclassification priceclassification svmhyperperameter cvscoring selectkbes

Updated Sep 5, 2022
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ShubhamKukreti07 / Mobile-Price-Classification-Machine-Learning

python machine-learning-algorithms logistic-regression decision-trees svm-classifier random-forest-classifier mobilepriceclassification

Updated Aug 18, 2024
Jupyter Notebook

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