Showing 1574 open source projects for "spreadsheet machine learning"

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  • 1
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  • 2
    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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  • 3
    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. ...
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  • 4

    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/
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  • 5
    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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  • 6
    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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  • 7
    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.
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  • 8

    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...
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  • 9

    Java Library for Machine Learning

    A pure Java library for machine learning

    JML is a machine learning library in Java, it is a pure Java package, and thus is cross-platform. The goal of JML is to make machine learning methods very easy to use and speed up code conversion from MATLAB to Java. Please be noted that JML has been replaced by LAML.
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  • 10
    Scene
    Scene is a computer vision framework that performs background subtraction and object tracking, using two traditional algorithms and three more recent algorithms based on neural networks and fuzzy classification rules. For each detected object, Scene sends TUIO messages to one or several client applications. The present release features GPU accelerated versions of all the background subtraction methods and morphological post processing of the object blobs with dilation and erosion filters,...
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  • 11
    Part-of-speech tagging is the task of assigning symbols from a particular set to words in a natural language text. ACOPOST implements and extends well-known machine learning techniques and provides a uniform environment for testing.
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  • 12

    TrackMania Challenge Generator

    Challenge generator for racing game 'TrackMania Nations Forever'

    A small tool which generates infinite number of different challenges for racing game 'TrackMania Nations Forever'. Currently only "Stadium" environment is supported. Latest release: 1.0.1.0, both English and Chinese version available.
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  • 13
    PyML is an interactive object oriented framework for machine learning written in python. PyML focuses on kernel classifiers, providing tools for feature selection, model selection, and methods for assessing classifier performance.
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  • 14

    Adaptive Difficulty Chinese Chess

    A Chinese chess game including an adaptive computer opponent.

    This project is an application of POSM algorithm on Chinese chess computer player. A computer player is implemented, which will adapt to the its opponent by adjusting its playing strength accordingly.
    Downloads: 0 This Week
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  • 15
    KMBOX - Kernel Methods Toolbox

    KMBOX - Kernel Methods Toolbox

    A collection of kernel-based algorithms for Matlab.

    KMBOX is a collection of MATLAB programs that implement kernel-based algorithms, with a focus on regression algorithms and online algorithms. It can be used for nonlinear signal processing and machine learning.
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  • 16
    Scikit Learn
    Machine Learning framework in Python
    Downloads: 121 This Week
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  • 17
    Virtual Eyewear

    Virtual Eyewear

    An eyewear trying simulator

    Try this software and find out the eyewear style that is the most suitable for you.
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  • 18

    GI-ICA

    Matlab implementation of GI-ICA and PEGI

    This is a matlab implementation of the GI-ICA algorithm for ICA in the presence of an additive Gaussian noise. The algorithm is discussed in the paper "Fast Algorithms for Gaussian Noise Invariant Independent Component Analysis" by James Voss, Luis Rademacher, and Mikhail Belkin.
    Downloads: 0 This Week
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  • 19
    openModeller is a complete C++ framework for species potential distribution modelling. The project also includes a graphical user interface, a web service interface and an API for Python.
    Downloads: 1 This Week
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  • 20

    CILP++

    In-development neural-symbolic system, CILP++

    This is the project of the extension of the original C-IL2P neural-symbolic system, CILP++, for reasoning, knowledge extraction and theory revision from propositional and first-order logics. *** ATTENTION! The CILP++ project has been discontinued from SVN! It has been migrated to Github on https://github.com/manoelfranca/cilppp!
    Downloads: 0 This Week
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  • 21
    Awesome Recurrent Neural Networks

    Awesome Recurrent Neural Networks

    A curated list of resources dedicated to RNN

    A curated list of resources dedicated to recurrent neural networks (closely related to deep learning). Provides a wide range of works and resources such as a Recurrent Neural Network Tutorial, a Sequence-to-Sequence Model Tutorial, Tutorials by nlintz, Notebook examples by aymericdamien, Scikit Flow (skflow) - Simplified Scikit-learn like Interface for TensorFlow, Keras (Tensorflow / Theano)-based modular deep learning library similar to Torch, char-rnn-tensorflow by sherjilozair, char-rnn...
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  • 22
    HLearn

    HLearn

    Homomorphic machine learning

    HLearn is a Haskell-based machine learning library focused on composability, algebraic structure, and performance. It provides a functional approach to building machine learning algorithms by leveraging algebraic properties such as monoids and groups. This allows for parallel, incremental, and distributed computation in a mathematically consistent way. HLearn aims to provide implementations of common algorithms like k-means, naive Bayes, and others while maintaining the expressiveness and safety of the Haskell language.
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  • 23
    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. ...
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  • 24

    FENNIX

    Fast EXperimentation with Neural Networks

    FENNIX is a simulator of artificial neural networks written in Java. It allows you to easily describe a complete simulation by using a simple text script language or by adding nodes to a tree of tasks by using the graphical used interface. Moreover, FENNIX is composed of pluggable tools that can be easily modified in order to add new functionalities to the simulator.
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  • 25

    DE-HEoC

    DE-based Weight Optimisation for Heterogeneous Ensemble

    We propose the use of Differential Evolution algorithm for the weight adjustment of base classifiers used in weighted voting heterogeneous ensemble of classifier. Average Matthews Correlation Coefficient (MCC) score, calculated over 10-fold cross-validation, has been used as the measure of quality of an ensemble. DE/rand/1/bin algorithm has been utilised to maximize the average MCC score calculated using 10-fold cross-validation on training dataset. The voting weights of base classifiers are...
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