SpecForesight: A Predictive Analytics Pipeline for Laptop Price Forecasting

Year : 2026 | Volume : 17 | Issue : 01 | Page : 61 71
    By

    Bhargav Chebrolu,

  1. Research Scholar, MS in Supply Chain Management (Naveen Jindal School of Management), The University of Texas, Dallas, Richardson, TX 75080, Dallas, United States

Abstract

This paper frames laptop pricing as a supervised predictive analytics problem, transforming product specifications into feature-rich signals to forecast price with calibrated regression models and operational guardrails against drift. A structured pipeline ingests tabular listings, performs data cleaning, and engineers domain-informed features (e.g., central processing unit (CPU) family and clocks, graphics processing unit (GPU) tiering, memory/storage density, display, and touch capabilities), followed by encoding and normalization to optimize model learnability. Multiple learners are benchmarked under cross-validated protocols—spanning linear baselines and non-linear ensembles—with model selection guided by out-of-sample R² and mean absolute error (MAE), residual diagnostics, and segment-wise error profiling across device categories. The chosen model is calibrated and threshold-governed to stabilize predictions under changing spec distributions, then exposed via a lightweight web interface to support counterfactual “what-if” pricing scenarios for unseen configurations. Contributions include an end-to-end, production-oriented specification-to-price pipeline, a comparative evaluation suite emphasizing generalization and interpretability, and a deployment pattern enabling real-time inference and scenario simulation. By centering forecasting rigor, error governance, and decision readiness, the work advances a practical blueprint for price prediction in consumer electronics grounded in predictive analytics principles.

Keywords: Price prediction, machine learning, regression analysis, feature engineering, random forest, consumer electronics

[This article belongs to Journal of Computer Technology & Applications ]

How to cite this article:
Bhargav Chebrolu. SpecForesight: A Predictive Analytics Pipeline for Laptop Price Forecasting. Journal of Computer Technology & Applications. 2026; 17(01):61-71.
How to cite this URL:
Bhargav Chebrolu. SpecForesight: A Predictive Analytics Pipeline for Laptop Price Forecasting. Journal of Computer Technology & Applications. 2026; 17(01):61-71. Available from: https://journals.stmjournals.com/jocta/article=2026/view=235960


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Regular Issue Subscription Review Article
Volume 17
Issue 01
Received 05/01/2026
Accepted 10/01/2026
Published 15/01/2026
Publication Time 10 Days
132

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