K-means clustering is one of the most approachable unsupervised learning techniques for finding patterns in unlabeled data. With Python’s scikit-learn and pandas, you can prepare, model, and evaluate ...

From implementing KNN, PCA, and clustering to applying deep learning and scientific tuning, these resources show how to build, refine, and optimize machine learning models. They combine hands-on ...

Introduction Lung cancer remains the leading cause of cancer mortality worldwide despite advances in treatment. Patient-related factors beyond tumour characteristics may influence prognosis but are ...

Unsupervised learning is a branch of machine learning that focuses on analyzing unlabeled data to uncover hidden patterns, structures, and relationships. Unlike supervised learning, which requires pre ...

ABSTRACT: This work describes a data integration model using the Statistical Matching methodology (hot deck distance) to integrate two surveys conducted by ISTAT (EU-SILC) and the Bank of Italy ...

Abstract: Most clustering algorithms require setting one or more parameters, which rely on prior knowledge or are constantly adjusted based on external indicators. To address the issues of requiring ...

Abstract: Clustering analysis has been widely applied in various fields, and boundary detection based clustering algorithms have shown effective performance. In this work, we propose a clustering ...