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UCI Machine Learning Repository

PulseAugur coverage of UCI Machine Learning Repository — every cluster mentioning UCI Machine Learning Repository across labs, papers, and developer communities, ranked by signal.

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RECENT · PAGE 1/1 · 6 TOTAL
  1. TOOL · CL_259234 ·

    Tabular Deep Learning Models Compared to Classical ML for Land Cover Classification

    A new research paper compares the effectiveness of tabular deep learning (TDL) models against classical machine learning algorithms for urban land cover classification. The study utilized the ULC dataset from the UCI Ma…

  2. TOOL · CL_216073 ·

    AI framework enhances bankruptcy prediction using ensemble models and XAI

    Researchers have developed a novel framework for predicting bankruptcy by combining feature selection, hybrid resampling techniques, and stacking ensemble models with explainable AI (XAI). The study utilized the Taiwane…

  3. TOOL · CL_200151 ·

    New benchmark CoMedBench evaluates synthetic medical data utility

    Researchers have introduced CoMedBench, a new benchmark designed to evaluate the fidelity and utility of synthetic medical data. This benchmark aims to address the challenges of using real patient data due to privacy re…

  4. TOOL · CL_147431 ·

    New cGAP framework visualizes high-dimensional categorical data

    Researchers have developed a new visualization framework called cGAP (categorical Generalized Association Plots) designed to effectively display high-dimensional categorical data. This method uses Homogeneity Analysis (…

  5. RESEARCH · CL_21773 ·

    PUICL transformer enables in-context positive-unlabeled learning without fitting

    Researchers have developed PUICL, a pretrained transformer model capable of performing positive-unlabeled (PU) learning through in-context learning. This approach eliminates the need for dataset-specific training or ite…

  6. TOOL · CL_16141 ·

    Researchers combine physics models with ML for better noninvasive blood pressure monitoring

    Researchers have developed a novel hybrid approach combining Windkessel models with machine learning to improve noninvasive blood pressure monitoring. This method integrates physical principles into data-driven models, …