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  1. Probabilistic Models in Machine Learning - GeeksforGeeks

    May 29, 2023 · Probabilistic models are an essential component of machine learning, which aims to learn patterns from data and make predictions on new, unseen data. They are statistical …

  2. Clustering in Machine Learning - GeeksforGeeks

    Jan 27, 2025 · In this guide, we'll learn understand concept of clustering, its applications, and some popular clustering algorithms. What is Clustering? The task of grouping data points …

  3. An Insight on Probabilistic Clustering in Machine Learning

    May 13, 2025 · Learn about probabilistic clustering in machine learning. Explore the key model-based approaches and how they improve clustering accuracy and data analysis.

  4. Probabilistic Model-Based Clustering in Data Mining

    Dec 5, 2024 · Model based clustering is an advanced technique used to group data points into clusters using statistical approach. Explore how model based clustering works and its benefits …

  5. Machine Learning - Distribution-Based Clustering

    Distribution-based clustering algorithms, also known as probabilistic clustering algorithms, are a class of machine learning algorithms that assume that the data points are generated from a …

  6. Probabilistic Clustering Models | DataScienceBase

    Explore probabilistic clustering models that leverage statistical frameworks to assign probabilities to cluster memberships. Understand models like Gaussian Mixture Models, Dirichlet Process …

  7. Probabilistic Cluster - an overview | ScienceDirect Topics

    A probabilistic cluster, in the context of computer science, is a hidden category that represents a distribution over the data space. It is inferred from a data set using a probability density …

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  8. Probabilistic Model in Machine Learning - Tpoint Tech - Java

    Mar 17, 2025 · Probabilistic models are used in a variety of machine learning tasks such as classification, regression, clustering, and dimensionality reduction. Some popular probabilistic …

  9. Probabilistic model-based clustering techniques have been widely used and have shown promis-ing results in many applications, ranging from image segmentation [71, 15], handwriting recog …

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  10. In this study, we introduce a novel algorithm called Powered Outer Probabilistic Clustering, show how it works through back-propagation (starting with many clusters and ending with an optimal …

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