Search Results for "spreadsheet machine learning" - Page 65
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Showing 2009 open source projects for "spreadsheet machine learning"
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PSGMiner a novel software which has been developed to carry out feature extraction in order that robust analysis and classification of various sleep diseases can be performed using polysomnographic data.The software is composed of different modules: The database, feature extraction, annotation,artifact and machine learning modules. for cite İlhan Umut, PSGMiner: A modular software for polysomnographic analysis, Computers in Biology and Medicine, Volume 73, 1 June 2016, Pages 1-9, ISSN 0010-4825, http://dx.doi.org/10.1016/j.compbiomed.2016.03.023. (//www.sciencedirect.com/science/article/pii/S0010482516300750) Keywords: Computer software; Digital signal processing; Machine learning; Polysomnography APPLICATIONS Medicine: diagnosis (neurophysiology, sleep disorders tests…) Research: biomedical engineering, signal processing and machine learning Educational
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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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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 Please be noted that JML has been replaced by LAML.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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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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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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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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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. -
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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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classify-20-NG-with-4-ML-Algo
Problem involves classifying 20000 messages into different 20 classes
This classification problem involves classifying 20000 messages into 20 different classes. The dataset can be found here: https://archive.ics.uci.edu/ml/datasets/Twenty+Newsgroups. Four Machine Learning algorithms; Naïve Bayes, Logistic Regression, Regularized Logistic Regression Support Vector Machine (SVM) were implemented and there training and test dataset accuracy were compared. Arguably, one of the most important aspect to solving this problem is having the appropriate data set format. Each of these algorithms has its peculiar data format; the specific format and how to reconstruct the entire dataset are illustrated in other sections below. ... -
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Machine Learning framework in Python
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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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Michel Max Spread - XLSX Loader/Creator
Michel Max MMSpread is an API XLSX files without the MS Excel ins...
The Michel Max - MMSpread is an API to generate XLSX Spreadsheets without having the Microsoft Excel installed in the Machine. It allows you to Load XLSX files and edit them, or even create them from nothing, without having annoying alerts when it is open. It supports the following Microsoft Excel items: - All styles (font, border, background, etc). - Validation: List ONLY, and it has to be sequential. - Conditional Formula Formatting. - Comments. - Number Format. Extra... -
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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. -
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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.
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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! -
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ankus
Data Mining and Machine Learning Algorithms based on MapReduce
[The feature of ankus] * ankus is a 'web-based big data mining project and tool'. - MapReduce-based data mining/machine learning algorithms library - Hadoop-based distributed bigdata system - offering a web-based GUI for easy use [The ankus project & License] * The ankus project consists of three as an open source. * ankus has Dual licensed under the community and commercial licenses. * community license is following GPLv3 - Some algorithms in Core Project do not under the OSS License [Demonstration Site] http://www.openankus.org:18080 [Official website & E-mail] www.openankus.org ankus@openankus.org [ankus video list] http://bit.ly/ankus_video [community] http://www.facebook.com/groups/openankus (Korean Groups) http://www.facebook.com/openankus (English Groups) http://bit.ly/ankus_forum (Google groups user forum) -
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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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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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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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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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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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ilodids
Incremental and local outlier detection
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json Validator Command line
Validate common syntax errors in json files from the command line
...Our new json validator, vbag, gives users the ability to scan multiple json files at once by doing any of the following: --specify the .json file to be scanned on the command line --specify a list file containing the list of json files to be scanned --specify a common name in all the json files you wish to scan (if you're in the same directory they're in) --automatically scans all recently modified json files it finds, if using github. Benefits of our json validator: -- Installs cleanly on your hosts - no need for any extra modules, libraries or packages -- There is no learning curve -- Runs locally on your machine -- You never have to leave the network -- No need to copy/paste to someone else's server -- More secure, will not be in someone else's webcache -- Not having to copy / paste files to jsonlint each time you wish to verify a long list of json files -
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...Mitchell's book (Machine Learning, Tom Mitchell) 2. Please download the data from http://www.cs.cmu.edu/afs/cs/project/theo-11/www/naive-bayes.html Report: A Comprehensive Report below: "20 newsgroup Classification problem" Accuracy: 83.625% Number of Training data: 50% of Total document chosen sequentially Number of Training data: 50% of remaining document Download the code and other necessary files in the Files Tab.
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This site contains four packages of Mass and mass-based density estimation. 1. The first package is about the basic mass estimation (including one-dimensional mass estimation and Half-Space Tree based multi-dimensional mass estimation). This packages contains the necessary codes to run on MATLAB. 2. The second package includes source and object files of DEMass-DBSCAN to be used with the WEKA system. 3. The third package DEMassBayes includes the source and object files of a Bayesian...
