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2 articles for “semi-supervised learning”
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Advances in Machine Learning and Data Analytics: A Multidisciplinary Synthesis
Abstract: Machine learning has emerged as a key driver of innovation across a wide range of fields. Its transformative potential is evident in natural language processing, computer vision, and real-time automation, where it addresses intricate challenges with remarkable efficiency. This paper delves into recent developments in machine learning, spotlighting techniques, such as semi-supervised learning frameworks, stable diffusion models for generative tasks, and advanced lightweight architecture for real-time defection detection. By integrating …
Published in International Journal of Distributed Computing and Technology · Vol. 11, Issue 1, 2025 · pp. 12–17 Read article
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Review of Feature Selection Methods and Semi Supervised Feature Selection Algorithms for Classification
Abstract: Current evolution in technology has resulted in tremendous growth of data with respect to dimensionality and sample size. Knowledge discovery from these high dimensional data are becoming cumbersome. Though powerful machine learning algorithms are prevalent, noisy data, imperfect sensing and collection of data leads to poor and defective knowledge discovery. Noise and redundant features cannot be circumvented due to which data collection process is biased. Dimensionality reduction techniques namely feature …
Published in International Journal of Software Computing and Testing · Vol. 6, Issue 1, 2020 · pp. 39–51 Read article