Search Results for "statistical"
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Showing 21 open source projects for "statistical"
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DataFrame
C++ DataFrame for statistical, Financial, and ML analysis
...For example, you would compare this to Pandas, R data.frame, or Polars. You can slice the data in many different ways. You can join, merge, and group-by the data. You can run various statistical, summarization, financial, and ML algorithms on the data. You can add your custom algorithms easily. You can multi-column sort, custom pick, and delete the data. DataFrame also includes a large collection of analytical algorithms in the form of visitors. These are from basic stats such as Mean, and Std Deviation and return, … to more involved analysis such as Affinity Propagation, Polynomial Fit, and Fast Fourier transform of arbitrary length … including a good collection of trading indicators. ... -
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ROOT
Analyzing, storing and visualizing big data, scientifically
...ROOT provides a very efficient storage system for data models, that demonstrated to scale at the Large Hadron Collider experiments: Exabytes of scientific data are written in columnar ROOT format. ROOT comes with histogramming capabilities in an arbitrary number of dimensions, curve fitting, statistical modeling, and minimization, to allow the easy setup of a data analysis system that can query and process the data interactively or in batch mode, as well as a general parallel processing framework, RDataFrame, that can considerably speed up an analysis. -
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Simd Library
C++ image processing and machine learning library with using of SIMD
The Simd Library is a free open-source image processing and machine learning library, designed for C and C++ programmers. It provides many useful high-performance algorithms for image processing such as pixel format conversion, image scaling and filtration, extraction of statistical information from images, motion detection, object detection and classification, neural networks. The algorithms are optimized with using of different SIMD CPU extensions. In particular, the library supports the following CPU extensions: SSE, AVX, AVX-512, and AMX for x86/x64, and NEON for ARM. The Simd Library has C API and also contains useful C++ classes and functions to facilitate access to C API. ... -
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Meshwork Analysis terminal
Quantitative analytical Finance Terminal
MWA Finance Terminal allows users to research and obtain data about various financial instruments and allows them to perform Statistical analysis with Various ML Technologies. It's divided into Modules and Options within them. -
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stkpp
C++ Statistical ToolKit
STK++ (http://www.stkpp.org) is a versatile, fast, reliable and elegant collection of C++ classes for statistics, clustering, linear algebra, arrays (with an Eigen-like API), regression, dimension reduction, etc. Some functionalities provided by the library are available in the R environment as R functions (http://cran.at.r-project.org/web/packages/rtkore/index.html). At a convenience, we propose the source packages on sourceforge. The library offers a dense set of (mostly) template... -
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Uranie
Uranie is CEA's uncertainty analysis platform, based on ROOT
Uranie is a sensitivity and uncertainty analysis plateform based on the ROOT framework (http://root.cern.ch) . It is developed at CEA, the French Atomic Energy Commission (http://www.cea.fr). It provides various tools for: - data analysis - sampling - statistical modeling - optimisation - sensitivity analysis - uncertainty analysis - running code on high performance computers - etc. Thanks to ROOT, it is easily scriptable in CINT (c++ like syntax) and Python. Is is available both for Unix and Windows platforms (a dedicated platform archive is available on request). Note : if you have downloaded version 3.12 before the 8th of february, a patch exists for a minor bug on TOutputFileKey file, don't hesitate to ask us. -
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Presage
the intelligent predictive text entry platform
...Presage computes probabilities for words which are most likely to be entered next by merging predictions generated by the different predictive algorithms. Presage's modular and extensible architecture allows its language model to be extended and customized to utilize statistical, syntactic, and semantic predictive algorithms. Presage's predictive capabilities are implemented by predictive plugins. Predictive plugins use services provided by the platform to implement multiple prediction techniques. -
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2D Statistical Models. Building: shape model, texture model and concatenated appearance model; Fitting: 1D profile ASM, 2D profile ASM, direct local texture constrained(LTC) ASM, basic AAM, ICIA AAM, IAIA AAM, etc.
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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. -
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Adaptive Gaussian Filtering
Machine learning with Gaussian kernels.
Libagf is a machine learning library that includes adaptive kernel density estimators using Gaussian kernels and k-nearest neighbours. Operations include statistical classification, interpolation/non-linear regression and pdf estimation. For statistical classification there is a borders training feature for creating fast and general pre-trained models that nonetheless return the conditional probabilities. Libagf also includes clustering algorithms as well as comparison and validation routines. ... -
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The Thot toolkit repository has moved to http://daormar.github.io/thot/ Thot is a toolkit for statistical machine translation. The new Thot toolkit includes fully automatic and interactive machine translation, incremental training of statistical models, parallel estimation, ...
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DeSR is a multilingual statistical dependency parser. It produces dependency parse trees for natural language sentences using a parsing model learned from annotated corpora.
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The Moses repository has moved: https://github.com/moses-smt/mosesdecoder Factored phrase-based, hierarchical and syntax decoder for statistical machine translation
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jaf_Kernels
Similarity Word-Sequence Kernels for Sentence Clustering toolkit
This project implements the techniques used in this paper: @INPROCEEDINGS{Andres10a, author = {Jesús Andrés-Ferrer and Germán Sanchis-Trilles and Francisco Casacuberta}, title = {Similarity Word-Sequence Kernels for Sentence Clustering}, booktitle = {Proceedings of the 8th International Workshop on Statistical Pattern Recognition}, year = {2010}, } This project depends on jaf_Utils: http://sourceforge.net/projects/jafutils/ Install it prior installation of jaf_Kernels. -
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Alchemy is a software package providing a series of algorithms for statistical relational learning and probabilistic logic inference, based on the Markov logic representation.
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Headrand is a static library wrote in c that contains functions to simulate complex systems or make statistical analysis with a new approach called "random function computing"
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Maximum entropy is a powerful method for constructing statistical models of classification tasks, such as part of speech tagging in Natural Language Processing. Several example applications using maxent can be found in the OpenNLP Tools Library.
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Fast machine learning and statistical methods library aimed at analyzing, understanding, and predicting information and trends within large data sets
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Collection of Statistical Language Processing Tools and Modules for Information Retrieval, Document Classification, Vectorization, Pattern Matching, Knowledge/Text Mining related problems.
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Mood is a framework to build decoder for statistical machine translation. It is modular and object-oriented to ease customization.
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Statistical Casting Daemon
SCASTD (Statistical Casting Daemon)
SCASTD (Statistical Casting Daemon) is a lightweight, high-performance statistics collection and analytics engine we designed specifically for streaming media infrastructure. Unlike traditional streaming servers, we built SCASTD to be the definitive monitoring solution that bridges legacy and modern streaming protocols, providing unified analytics across your entire streaming ecosystem
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