Work

Predicting Parcel Damage Through Pattern Extraction and Machine Learning

Year: 2025

Type: article

Abstract: This research explores parcel-damage prediction using multiple pattern-extraction methods, including Apriori, FP-Growth, K-Means clustering, logistic regression, and a custom linear-algebra–based approach, for both pattern observation or direct prediction.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.17717915

Author: Falouti, Zine El Abidine

Language: English

Topic: Data Mining and Machine Learning Applications

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W7106799185

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