Showing 34 open source projects for "data mining"

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  • 1
    Orange Data Mining

    Orange Data Mining

    Orange: Interactive data analysis

    ...When teaching data mining, we like to illustrate rather than only explain.
    Downloads: 33 This Week
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  • 2
    Awesome Fraud Detection Research Papers

    Awesome Fraud Detection Research Papers

    A curated list of data mining papers about fraud detection

    A curated list of data mining papers about fraud detection from several conferences.
    Downloads: 2 This Week
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  • 3
    Scrapy

    Scrapy

    A fast, high-level web crawling and web scraping framework

    ...It can be used for data mining, monitoring and automated testing.
    Downloads: 23 This Week
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  • 4

    FreeSEM

    Free and open-source desktop application designed for SEM

    FreeSEM is a free, open-source desktop application designed for researchers and students to perform Structural Equation Modeling (SEM) for statistical and research analysis. It allows users to visually build models using a drag-and-drop interface to create path diagrams and analyze relationships between observed and latent variables. The software supports methods such as exploratory factor analysis, covariance-based SEM, partial least squares SEM, and meta-SEM, and it provides model fit...
    Downloads: 7 This Week
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  • 5
    paramspider

    paramspider

    Mine parameterized URLs from web archives for security testing

    ParamSpider is an open source command-line tool designed to discover URLs that contain parameters by mining historical data from web archives such as the Wayback Machine. It helps security researchers, penetration testers, and bug bounty hunters collect potential attack surfaces by automatically gathering archived URLs related to a specific domain. Instead of returning every discovered URL, the tool intelligently filters results to highlight parameterized endpoints that are more useful for vulnerability testing. ...
    Downloads: 1 This Week
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  • 6
    Karate Club

    Karate Club

    An API Oriented Open-source Python Framework for Unsupervised Learning

    Karate Club is an unsupervised machine learning extension library for NetworkX. Karate Club consists of state-of-the-art methods to do unsupervised learning on graph-structured data. To put it simply it is a Swiss Army knife for small-scale graph mining research. First, it provides network embedding techniques at the node and graph level. Second, it includes a variety of overlapping and non-overlapping community detection methods. Implemented methods cover a wide range of network science (NetSci, Complenet), data mining (ICDM, CIKM, KDD), artificial intelligence (AAAI, IJCAI) and machine learning (NeurIPS, ICML, ICLR) conferences, workshops, and pieces from prominent journals.
    Downloads: 0 This Week
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  • 7
    Pattern

    Pattern

    Web mining module for Python, with tools for scraping

    Pattern is an open-source Python library that provides tools for web mining, natural language processing, machine learning, and network analysis. The project integrates multiple capabilities into a single framework that allows developers to collect, process, and analyze textual data from the web. It includes modules for web scraping and crawling that can retrieve information from sources such as social media platforms, search engines, and online knowledge bases.
    Downloads: 0 This Week
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  • 8
    OmicSelector

    OmicSelector

    Feature selection and deep learning modeling for omic biomarker study

    OmicSelector is an environment, Docker-based web application, and R package for biomarker signature selection (feature selection) from high-throughput experiments and others. It was initially developed for miRNA-seq (small RNA, smRNA-seq; hence the name was miRNAselector), RNA-seq and qPCR, but can be applied for every problem where numeric features should be selected to counteract overfitting of the models. Using our tool, you can choose features, like miRNAs, with the most significant...
    Downloads: 0 This Week
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  • 9
    JSONVisor

    JSONVisor

    Visor for mass spectrometry JSON files generated by Integrator

    ...For more information, you can have a look at the README.md file in the source code tree: https://sourceforge.net/p/lp-csic-uab/jsonvisor3/code/ci/default/tree/README.md - Gallardo, Ó., Ovelleiro, D., Gay, M., Carrascal, M., & Abian, J. (2014). A collection of open source applications for mass spectrometry data mining. PROTEOMICS, 14(20), 2275–2279. https://doi.org/10.1002/pmic.201400124
    Downloads: 0 This Week
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  • 10
    EasierMGF

    EasierMGF

    Converts RAW Thermo Files into MGF files

    ...For more information, you can have a look at the README.md file in the source code tree: https://sourceforge.net/p/lp-csic-uab/easiermgf3/code/ci/default/tree/README.md - Gallardo, Ó., Ovelleiro, D., Gay, M., Carrascal, M., & Abian, J. (2014). A collection of open source applications for mass spectrometry data mining. PROTEOMICS, 14(20), 2275–2279. https://doi.org/10.1002/pmic.201400124
    Downloads: 1 This Week
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  • 11
    LymPHOS2

    LymPHOS2

    LymPHOS2 Web-App

    ...Proteomics 2009, 9, 3741–3751. DOI: 10.1002/pmic.200800701 - Gallardo, Ó., Ovelleiro, D., Gay, M., Carrascal, M., Abian, J., A collection of open source applications for mass spectrometry data mining. Proteomics 2014, 20, 2275-2279. DOI: 10.1002/pmic.20140012
    Downloads: 0 This Week
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  • 12
    An open source framework for LC-MS based proteomics and metabolomics. OpenMS offers data structures and algorithms for the processing of mass spectrometry data. The library is written in C++. Our source code and wiki lives on GitHub (https://github.com/OpenMS/OpenMS).
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    Downloads: 7 This Week
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  • 13
    GEOMS2

    GEOMS2

    Geostatistics and geosciences modeling software

    ...attredirects=0&d=1 http://sourceforge.net/projects/geoms2/files/Mining.7z/download
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    Downloads: 11 This Week
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  • 14
    Siamese and triplet learning

    Siamese and triplet learning

    Siamese and triplet networks with online triplet mining in PyTorch

    ...The repository demonstrates how to train these models using contrastive loss and triplet loss functions, which encourage embeddings of similar samples to be close while pushing dissimilar samples farther apart. It includes data loaders, training scripts, neural network architectures, and evaluation metrics that allow researchers to experiment with different embedding learning strategies. The project also implements online pair and triplet mining techniques to efficiently generate training examples during model training.
    Downloads: 0 This Week
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  • 15

    PyDaMelo

    Python-compatible Data mining elementary objects

    An attempt at offering machine learning and data mining algorithms at the finest grain we are able to, easy to combine together through Python scripting to glue together the Lego-like bricks.
    Downloads: 0 This Week
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  • 16
    QAL

    QAL

    Query Abstraction Layer

    Project has moved to: https://github.com/OptimalBPM/qal QAL is a collection of libraries for mining, transforming and writing data from and to a number of places. Sources and destinations include different SQL and NoSQL backends, file formats like .csv, XML and excel. Even untidy HTML web pages. It has a database abstraction layer that supports connectivity to Postgres, MySQL, DB2, Oracle, MS SQL server. JSON and MongoDB is coming.
    Downloads: 0 This Week
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  • 17

    ExAM-Exome_Analysis_And_Mining

    A whole exome sequencing analysis package and its graphical interface

    During the past few years, whole exome sequencing has imposed itself for genetic research, largely due to its use for detection of causative mutations responsible for Mendelian disorders. As a consequence of their power and of the rapidly decreasing cost of these technologies, massive amount of exome sequencing data are generated and becoming available to a broadening community of scientists. However, these data remain difficult to analyze and interpret by the general scientific community,...
    Downloads: 0 This Week
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  • 18
    ExSTraCS

    ExSTraCS

    Extended Supervised Tracking and Classifying System

    This advanced machine learning algorithm is a Michigan-style learning classifier system (LCS) developed to specialize in classification, prediction, data mining, and knowledge discovery tasks. Michigan-style LCS algorithms constitute a unique class of algorithms that distribute learned patterns over a collaborative population of of individually interpretable IF:THEN rules, allowing them to flexibly and effectively describe complex and diverse problem spaces. ExSTraCS was primarily developed to address problems in epidemiological data mining to identify complex patterns relating predictive attributes in noisy datasets to disease phenotypes of interest. ...
    Downloads: 0 This Week
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  • 19

    Data analysis for ADEXL

    Create Excel reports from results of Cadence ADE-XL simulations

    *** Required files from "Excel COM API for Python" project *** The scripts allows post processing of data saved in CSV format from "Detail - Transposed" view of ADE-XL
    Downloads: 0 This Week
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  • 20

    SCaVis

    Scientific Computation and Visualization Environment

    SCaVis is an environment for scientific computation, data analysis and data visualization for scientists, engineers and students. The program is fully multiplatform (100% Java) and integrated with Java and a number of scripting languages: Jython (Python), Groovy, JRuby, BeanShell. SCaVis can be used to plot functions and data in 2D and 3D, perform statistical tests, data mining, numeric computations, function minimization, linear algebra, solving systems of linear and differential equations. ...
    Downloads: 2 This Week
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  • 21
    MRA

    MRA

    A general recommender system with basic models and MRA

    Multi-categorization Recommendation Adjusting (MRA) is to optimize the results of recommendation based on traditional(basic) recommendation models, through introducing objective category information and taking use of the feature that users always get the habits of preferring certain categories. Besides this, there are two advantages of this improved model: 1) it can be easily applied to any kind of existing recommendation models. And 2) a controller is set in this improved model to provide...
    Downloads: 1 This Week
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  • 22

    cuckoo2mist

    Malware Instruction Set

    The Malware Instruction Set (MIST) is a representation for monitored behavior of malicious software. The representation is optimized for effective and efficient analysis of behavior using data mining and machine learn- ing techniques. It can be obtained automatically during analysis of malware with a behavior monitoring tool or by converting existing behavior reports. The representation is not restricted to a particular monitoring tool and thus can also be used as a meta language to unify behavior reports of different sources. ...
    Downloads: 0 This Week
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  • 23
    GISBox by Citiviz

    GISBox by Citiviz

    Ready-to-use appliance for GIS, Data Mining and Analysis, Modelling...

    GISBox by Citiviz is a ready-to-use virtual appliance containing an assortment of powerful, free and open source GIS, Data Mining and Analysis, Modelling and Programming software and packages. The pre-configured and tested GISBox allows you to try and use in few minutes a variety of software used by data scientists, engineers, physicists, mathematicians, geomatics engineers, and geographers from around the globe, without installing anything more than once the Oracle VirtualBox™ software (https://www.virtualbox.org/) on your Linux, Windows or Mac computer. ...
    Downloads: 0 This Week
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  • 24
    Math tools in Python to tackle down problems in Operational Research fields. Comes with a Django based web interface to allow remote access to complex simulation means.
    Downloads: 0 This Week
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  • 25
    ViAmI-Server

    ViAmI-Server

    Pattern recognition for ADL events

    This software uses computer vision algorithms for mining sequence data from telemonitoring data with CBRs. We propose an approach which treats the detection of changes in behavior detected with a sensor/video fusion, which occur at radically different time-scales, through a CBR in two levels: low and high level. The system is always updating the database with the daily data.
    Downloads: 0 This Week
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