Search Results for "spreadsheet machine learning" - Page 64

Showing 2009 open source projects for "spreadsheet machine learning"

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  • 1

    jPrediction

    Open project ternary classifier of the machine learning

    Open project ternary classifier of the machine learning
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  • 2
    Density-ratio based clustering

    Density-ratio based clustering

    Discovering clusters with varying densities

    This site provides the source code of two approaches for density-ratio based clustering, used for discovering clusters with varying densities. One approach is to modify a density-based clustering algorithm to do density-ratio based clustering by using its density estimator to compute density-ratio. The other approach involves rescaling the given dataset only. An existing density-based clustering algorithm, which is applied to the rescaled dataset, can find all clusters with varying...
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  • 3
    Apache PredictionIO

    Apache PredictionIO

    Machine learning server for developers and ML engineers

    Apache PredictionIO® is an open source Machine Learning Server built on top of a state-of-the-art open source stack for developers and data scientists to create predictive engines for any machine learning task. Quickly build and deploy an engine as a web service on production with customizable templates; respond to dynamic queries in real-time once deployed as a web service; evaluate and tune multiple engine variants systematically; unify data from multiple platforms in batch or in real-time for comprehensive predictive analytics; speed up machine learning modeling with systematic processes and pre-built evaluation measures; support machine learning and data processing libraries such as Spark MLLib and OpenNLP; implement your own machine learning models and seamlessly incorporate them into your engine; simplify data infrastructure management.
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  • 4
    PredictionIO

    PredictionIO

    Machine learning server for building predictive applications

    Apache PredictionIO is an open-source machine learning server designed to simplify the process of building and deploying predictive engines. It offers a scalable infrastructure with support for multiple ML algorithms, event data collection, and deployment workflows. Developers can use templates or build custom engines, making it a flexible solution for integrating machine learning into applications.
    Downloads: 0 This Week
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  • 5
    Mass-based dissimilarity

    Mass-based dissimilarity

    A data dependent dissimilarity measure based on mass estimation.

    This software calculates the mass-based dissimilarity matrix for data mining algorithms relying on a distance measure. References: Overcoming Key Weaknesses of Distance-based Neighbourhood Methods using a Data Dependent Dissimilarity Measure. KDD 2016 http://dx.doi.org/10.1145/2939672.2939779 The source code, presentation slide and poster are attached under "Files". The presentation video in KDD 2016 is published on https://youtu.be/eotD_-SuEoo . Since this software is licensed...
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  • 6
    Community Detection Modularity Suite

    Community Detection Modularity Suite

    Suite of community detection algorithms based on Modularity

    - MixtureModel_v1r1: overlapping community algorithm [3], which includes novel partition density and fuzzy modularity metrics. - OpenMP versions of algorithms in [1] are available to download. - Main suite containing three community detection algorithms based on the Modularity measure containing: Geodesic and Random Walk edge Betweenness [1] and Spectral Modularity [2]. Collaborator: Theologos Kotsos. [1] M. Newman & M. Girvan, Physical Review, E 69 (026113), 2004. [2] M....
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  • 7
    JCLAL

    JCLAL

    A Java Class Library for Active Learning

    ...The full citation is: Oscar Reyes, Eduardo Pérez, María del Carmen Rodríguez-Hernández, Habib M. Fardoun, Sebastián Ventura. JCLAL: A Java Framework for Active Learning. Journal of Machine Learning Research, 17(95):1-5, 2016.
    Downloads: 0 This Week
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  • 8
    Convolution arithmetic

    Convolution arithmetic

    A technical report on convolution arithmetic in deep learning

    A technical report on convolution arithmetic in the context of deep learning. The code and the images of this tutorial are free to use as regulated by the licence and subject to proper attribution. The animations will be output to the gif directory. Individual animation steps will be output in PDF format to the pdf directory and in PNG format to the png directory. We introduce a guide to help deep learning practitioners understand and manipulate convolutional neural network architectures....
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  • 9
    Question Answering Corpus

    Question Answering Corpus

    Question answering dataset in "Teaching Machines to Read & Comprehend"

    ...The dataset, introduced in the 2015 paper “Teaching Machines to Read and Comprehend” (Hermann et al., NIPS 2015), was among the first large corpora designed to train and evaluate machine reading and comprehension models. The repository provides scripts for downloading archived CNN and Daily Mail articles from the Wayback Machine and automatically generating cloze-style questions where entities in the text are replaced with placeholders. Each data instance consists of a news article (context), a generated question, and its corresponding answer, making it suitable for supervised machine learning setups. ...
    Downloads: 8 This Week
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  • 10
    e-Metis - ML

    e-Metis - ML

    Modul za napovedovanje učnih težav.

    Downloads: 0 This Week
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  • 11
    SNooPer
    A machine learning-based method for somatic variant identification from low-pass next-generation sequencing.
    Downloads: 0 This Week
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  • 12
    Phrasal

    Phrasal

    Statistical phrase-based machine translation system

    Stanford Phrasal is a state-of-the-art statistical phrase-based machine translation system, written in Java. At its core, it provides much the same functionality as the core of Moses. Distinctive features include: providing an easy to use API for implementing new decoding model features, the ability to translating using phrases that include gaps (Galley et al. 2010), and conditional extraction of phrase-tables and lexical reordering models. Developed by The Natural Language Processing Group...
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  • 13
    Data Science Specialization

    Data Science Specialization

    Course materials for the Data Science Specialization on Coursera

    ...The repository is designed as a shared space for code examples, datasets, and instructional materials, helping learners follow along with lectures and assignments. It spans essential topics such as R programming, data cleaning, exploratory data analysis, statistical inference, regression models, machine learning, and practical data science projects. By providing centralized resources, the repo makes it easier for students to practice concepts and replicate examples from the curriculum. It also offers a structured view of how multiple disciplines—programming, statistics, and applied data analysis—come together in a professional workflow.
    Downloads: 1 This Week
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  • 14

    sgmweka

    Weka wrapper for the SGM toolkit for text classification and modeling.

    Weka wrapper for the SGM toolkit for text classification and modeling. Provides Sparse Generative Models for scalable and accurate text classification and modeling for use in high-speed and large-scale text mining. Has lower time complexity of classification than comparable software due to inference based on sparse model representation and use of an inverted index. The provided .zip file is in the Weka package format, giving access to text classification. Other functions are usable through...
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    Downloads: 15 This Week
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  • 15
    RDKit

    RDKit

    Open-Source Cheminformatics and Machine Learning

    A collection of cheminformatics and machine-learning software written in C++ and Python. NOTE: the RDKit source code and downloads are now in github: https://github.com/rdkit/rdkit The core algorithms and data structures are written in C++. Wrappers are provided to use the toolkit from either Python or Java. Additionally, the RDKit distribution includes a PostgreSQL-based cartridge that allows molecules to be stored in relational database and retrieved via substructure and similarity searches.
    Downloads: 14 This Week
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    Downloads: 0 This Week
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  • 17
    Open Cezeri Library

    Open Cezeri Library

    Effective Linear Algebra and Computer Vision Library with JAVA

    ...To learn for library please try to use test examples at OpenCezeriLibrary\test\test. It is originally developed at el-cezeri laboratory of Siirt University, in order to establish generic framework of reusable components and software tools for machine vision, machine learning, AI and robotic applications. Currently, it holds following main concepts 1- Vision: It can access web cams, imaging source industrial cameras for manuel settings and advanced issues. Studies on accesing Leapmotion and Kinect is still under-development. 2- Machine learning: It uses Weka Software tool and some personel coded ML algorithms 3- CMatrix: Special matrix library called as CMatrix meaning Cezeri Maztrix Class. ...
    Downloads: 0 This Week
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  • 18
    Ampare Speech To Amaar and Martin

    Ampare Speech To Amaar and Martin

    Ampare Speech To Amaar and Martin Version 4 is an artificial intellige

    Ampare Speech To Amaar and Martin Version 4 is an artificial intelligence and machine learning software to make computers can be talk like a real human and learn from the human. that going to use in a robot in a future.
    Downloads: 0 This Week
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  • 19
    BPL

    BPL

    Bayesian Program Learning model for one-shot learning

    BPL (Bayesian Program Learning) is a MATLAB implementation of the Bayesian Program Learning framework for one-shot concept learning (especially on handwritten characters). The approach treats each concept (e.g. a character) as being generated by a probabilistic program (motor primitives, strokes, spatial relationships), and inference proceeds by fitting those generative programs to a single example, generalizing to new examples, and generating new exemplars. The repository contains code for...
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  • 20

    jLDADMM

    A Java package for the LDA and DMM topic models

    The Java package jLDADMM is released to provide alternative choices for topic modeling on normal or short texts. It provides implementations of the Latent Dirichlet Allocation topic model and the one-topic-per-document Dirichlet Multinomial Mixture model (i.e. mixture of unigrams), using collapsed Gibbs sampling. In addition, jLDADMM supplies a document clustering evaluation to compare topic models. See the usage of jLDADMM in its website at http://jldadmm.sourceforge.net/
    Downloads: 0 This Week
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  • 21
    A broad collection of command-line-interface tools for performing machine learning operations. Each tool is a thin wrapper around functionality in a well-documented C++ class library. Waffles tools are designed to be simple, script-friendly, and to
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  • 22
    DeepLearnToolbox

    DeepLearnToolbox

    Matlab/Octave toolbox for deep learning

    DeepLearnToolbox is a MATLAB / Octave toolbox for prototyping deep learning models. It provides implementations of feedforward neural networks, convolutional neural networks (CNNs), deep belief networks (DBNs), stacked autoencoders, convolutional autoencoders, and more. The toolbox includes example scripts for each method, enabling users to quickly experiment with architectures, training, and inference workflows. Although it's been flagged as deprecated and no longer actively maintained, it...
    Downloads: 6 This Week
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  • 23
    libcrn is document image processing library written in C++11 for Linux, Windows, Mac OsX and Google Android. It is a toolbox that allows to create easily software such as OCRs and layout analysis tools.
    Downloads: 0 This Week
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  • 24

    GA-EoC

    GeneticAlgorithm-based search for Heterogeneous Ensemble Combinations

    In data classification, there are no particular classifiers that perform consistently in every case. This is even worst in case of both the high dimensional and class-imbalanced datasets. To overcome the limitations of class-imbalanced data, we split the dataset using a random sub-sampling to balance them. Then, we apply the (alpha,beta)-k feature set method to select a better subset of features and combine their outputs to get a consolidated feature set for classifier training. To...
    Downloads: 0 This Week
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  • 25
    MCCCS

    MCCCS

    Multi Channel Classification and Clustering

    Here we present an image-based Multi Channel Classification and Clustering System (MCCCS). It is an generalized, script-based classification system for processing various kinds of image data. Due to the modular design, individual processing-components can be easily adapted, extended or exchanged by own extensions. See project website for installation instructions.
    Downloads: 0 This Week
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