Mobile Price With The Demand of The Mobile Phone Features Prediction using KNN

The approach of this work is based on the data science algorithms. Our model is able to predict the mobile price with the demand of the mobile phone features. We used a relavent and filtered algorithmic rules that can analyse the mobile phone price with it’s installed mobile phone feature. The resulting model was deployed and used as a mobile phone price prediction tool. The aim of the deployed application is to inform the mobile buyers about the mobile price range in advance to avoid the losses of money and fraudness of mobile company.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-09-28
DOI
https://doi.org/10.5281/zenodo.17220424
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
0.00
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article

Mobile Price With The Demand of The Mobile Phone Features Prediction using KNN

Zenodo (CERN European Organization for Nuclear Research)
Geochemistry and Geologic Mapping
article

Mobile Price With The Demand of The Mobile Phone Features Prediction using KNN

article en

Abstract

The approach of this work is based on the data science algorithms. Our model is able to predict the mobile price with the demand of the mobile phone features. We used a relavent and filtered algorithmic rules that can analyse the mobile phone price with it’s installed mobile phone feature. The resulting model was deployed and used as a mobile phone price prediction tool. The aim of the deployed application is to inform the mobile buyers about the mobile price range in advance to avoid the losses of money and fraudness of mobile company.

Zenodo (CERN European Organization for Nuclear Research)
University of Liberal Arts Bangladesh (BD), University of Salford (GB)
Peace, Justice and strong institutions
Openalex Percentile: Top 26%
Geochemistry and Geologic Mapping
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