Showing 4 open source projects for "matlab classification learner"

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  • 1
    Machine Learning Octave

    Machine Learning Octave

    MatLab/Octave examples of popular machine learning algorithms

    ...Code written so as to expose and comment on mathematical steps. The repository includes clustering, regression, classification, neural networks, anomaly detection, and other standard ML topics. Does not rely heavily on specialized toolboxes or library shortcuts.
    Downloads: 0 This Week
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  • 2
    Exclusively Dark Image Dataset

    Exclusively Dark Image Dataset

    ExDARK dataset is the largest collection of low-light images

    The Exclusively Dark (ExDARK) dataset is one of the largest curated collections of real-world low-light images designed to support research in computer vision tasks under challenging lighting conditions. It contains 7,363 images captured across ten different low-light scenarios, ranging from extremely dark environments to twilight. Each image is annotated with both image-level labels and object-level bounding boxes for 12 object categories, making it suitable for detection and classification...
    Downloads: 2 This Week
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  • 3
    Omniglot

    Omniglot

    Omniglot data set for one-shot learning

    This repository hosts the Omniglot dataset for one-shot learning, containing handwritten characters across multiple alphabets along with stroke data. It includes both MATLAB and Python starter scripts (e.g. demo.m, demo.py) to illustrate how to load the images and stroke sequences and run baseline experiments (such as classification by modified Hausdorff distance). The dataset provides both an image representation of each character and the time-ordered stroke coordinates ([x, y, t]) for each instance. ...
    Downloads: 1 This Week
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  • 4
    BudgetedSVM

    BudgetedSVM

    BudgetedSVM: A C++ Toolbox for Large-scale, Non-linear Classification

    We present BudgetedSVM, a C++ toolbox containing highly optimized implementations of three recently proposed algorithms for scalable training of Support Vector Machine (SVM) approximators: Adaptive Multi-hyperplane Machines (AMM), Budgeted Stochastic Gradient Descent (BSGD), and Low-rank Linearization SVM (LLSVM). BudgetedSVM trains models with accuracy comparable to LibSVM in time comparable to LibLinear, as it allows solving highly non-linear classi fication problems with millions of...
    Downloads: 0 This Week
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