Search Results for "classification" - Page 30
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Showing 774 open source projects for "classification"
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The Open Terminology Server projects main goals is provide a fully distribute terminology server which allows a client to navigate various classifications consistently via a generic classification model API (GAPI).
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Pattern recognition software package. It includes several classification and clustering algorithms. It can read data from a set of images, an ASCII file or a JDBC connection. A small TCP data server with its corresponding JDBC driver is included.
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The 'BandSystem' spectral analysis system is a rule-based system for the classification of mineral spectra. It consists of a preprocessor, a feature extractor, and a rule-based system to identify minerals from infra-red reflectance spectra.
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Books Library Automation System.<br> key features: <ul type="circle"> <li>book catalogue</li> <li>book classification (Dewey Decimal Classification)</li> <li>work with readers accounts<br> </ul>
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Minix is a Mp3 files manager. It uses ID3 tags informations to make a Mp3's classification in a treeview. It allows tags ID3v1 edition, filenames format, lyrics addition, etc.
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ApMl provides users with the ability to crawl the web and download pages to their computer in a directory structure suitable for a Machine Learning system to both train itself and classify new documents. Classification Algorithms include Naive Bayes, KNN
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WebSPHINX is a web crawler (robot, spider) Java class library, originally developed by Robert Miller of Carnegie Mellon University. Multithreaded, tollerant HTML parsing, URL filtering and page classification, pattern matching, mirroring, and more.
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Stereologist assists the medical researcher in the classification of microscopic tissue samples captured as digital image files. The data collected can then be exported to a spreadsheet for further analysis.
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pySPACE
Signal Processing and Classification Environment in Python using YAML
pySPACE is a modular software for processing of large data streams that has been specifically designed to enable distributed execution and empirical evaluation of signal processing chains. Various signal processing algorithms (so called nodes) are available within the software, from finite impulse response filters over data-dependent spatial filters (e.g. CSP, xDAWN) to established classifiers (e.g. SVM, LDA). pySPACE incorporates the concept of node and node chains of the MDP framework. Due... -
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NeuralNetwork
Neural Network for Classification Problems
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CATCH
Cell acqusition tracking classification and handling suite
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PhaseSpace.NET
CHAOTIC DATA MODELING AND CLASSIFICATION USING SUPERVISED LEARNING MET
CHAOTIC DATA MODELING AND CLASSIFICATION USING SUPERVISED LEARNING METHODS Klasifikace pomoci metody rekonstrukce fazoveho prostoru Petr Podhorsky, podhope1@fit.cvut.cz Prvni verze projektu, vytvorena za ucelem overeni, ze ma smysl metodu klasifikace pomoci rekonstrukce fazoveho prostoru dale zkoumat. Vysledky prezentovany v odborne studii vcetne vytyceni dalsich kroku. -
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LightGBM
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
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Infect is a network traffic classification tool, that classifies TCP protocols. The classification is based on ML techniques. Scen: Train/Recognize arbitrary protocols (SSH, HTTPS..), Detect policy violations (e.g. tunnels)
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DelphAI is a Delphi component inspired by Scikit-learn, designed to simplify the development of regression, classification, recommendation, and clustering solutions. Whether you're a beginner or an experienced Machine Learning practitioner, DelphAI makes the process simple and efficient, allowing you to focus on results rather than complex implementation.
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fashion-clip
CLIP model fine-tuned for zero-shot fashion product classification
FashionCLIP is a domain-adapted CLIP model fine-tuned specifically for the fashion industry, enabling zero-shot classification and retrieval of fashion products. Developed by Patrick John Chia and collaborators, it builds on the CLIP ViT-B/32 architecture and was trained on over 800K image-text pairs from the Farfetch dataset. The model learns to align product images and descriptive text using contrastive learning, enabling it to perform well across various fashion-related tasks without additional supervision. ... -
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roberta-base
Robust BERT-based model for English with improved MLM training
...It captures contextual representations of language by masking 15% of input tokens and predicting them. RoBERTa is designed to be fine-tuned for a wide range of NLP tasks such as classification, QA, and sequence labeling, achieving strong performance on the GLUE benchmark and other downstream applications. -
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ifscat is an Interactive Feature Selection and Classification Tool for image processing and segmentation.
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WiiGLELib = Wiimote Gesture Learning Environment Library. It provides a framework for the classification/recognition of the Wii controller gestures.
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A standalone, STL interface to the Torch library's Support Vector Machine (SVM). It supports single or multiclass (one vs. all) classification using dot product, polynomial, Gaussian and sigmoid kernels.
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t5-base
Flexible text-to-text transformer model for multilingual NLP tasks
t5-base is a pre-trained transformer model from Google’s T5 (Text-To-Text Transfer Transformer) family that reframes all NLP tasks into a unified text-to-text format. With 220 million parameters, it can handle a wide range of tasks, including translation, summarization, question answering, and classification. Unlike traditional models like BERT, which output class labels or spans, T5 always generates text outputs. It was trained on the C4 dataset, along with a variety of supervised NLP benchmarks, using both unsupervised denoising and supervised objectives. The model supports multiple languages, including English, French, Romanian, and German. ... -
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t5-small
T5-Small: Lightweight text-to-text transformer for NLP tasks
T5-Small is a lightweight variant of the Text-To-Text Transfer Transformer (T5), designed to handle a wide range of NLP tasks using a unified text-to-text approach. Developed by researchers at Google, this model reframes all tasks—such as translation, summarization, classification, and question answering—into the format of input and output as plain text strings. With only 60 million parameters, T5-Small is compact and suitable for fast inference or deployment in constrained environments. It was pretrained on the C4 dataset using both unsupervised denoising and supervised learning on tasks like sentiment analysis, NLI, and QA. ... -
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MathematicaForPrediction
Mathematica for prediction (packages and documents,)
Mathematica packages and related documents for the implementation and use of Machine Learning and Statistical algorithms used for prediction and personalization. Here is a closely related blog : https://mathematicaforprediction.wordpress.com .
