Search Results for "regression"
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Showing 50 open source projects for "regression"
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1
statsmodels
Statsmodels, statistical modeling and econometrics in Python
statsmodels is a Python module that provides classes and functions for the estimation of many different statistical models, as well as for conducting statistical tests, and statistical data exploration. An extensive list of result statistics are available for each estimator. The results are tested against existing statistical packages to ensure that they are correct. The package is released under the open source Modified BSD (3-clause) license. Generalized linear models with support for all... -
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PyTorch Geometric Temporal
Spatiotemporal Signal Processing with Neural Machine Learning Models
The library consists of various dynamic and temporal geometric deep learning, embedding, and Spatio-temporal regression methods from a variety of published research papers. Moreover, it comes with an easy-to-use dataset loader, train-test splitter and temporal snaphot iterator for dynamic and temporal graphs. The framework naturally provides GPU support. It also comes with a number of benchmark datasets from the epidemiological forecasting, sharing economy, energy production and web traffic management domains. ... -
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STK
a Small (Matlab/Octave) Toolbox for Kriging
The STK is a (not so) Small Toolbox for Kriging. Its primary focus in on the interpolation / regression technique known as kriging, which is very closely related to Splines and Radial Basis Functions, and can be interpreted as a non-parametric Bayesian method using a Gaussian Process (GP) prior. The STK also provides tools for the sequential and non-sequential design of experiments. Even though it is, currently, mostly geared towards the Design and Analysis of Computer Experiments (DACE), the STK can be useful for other applications areas (such as Geostatistics, Machine Learning, Non-parametric Regression, etc.). -
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Physical Symbolic Optimization (Φ-SO)
Physical Symbolic Optimization
Physical Symbolic Optimization (Φ-SO) - A symbolic optimization package built for physics. Symbolic regression module uses deep reinforcement learning to infer analytical physical laws that fit data points, searching in the space of functional forms. -
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5
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 classes in C++ and is suitable for projects ranging from small one-off projects to complete data mining application suites. -
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glslmath
C++ header-only library that simulates GLSL math
GLSLmath provides C++ math operations as defined by GLSL. For example, it provides methods to easily setup viewing transformations and perspective projections. GLSLmath has been inspired by the glm and slmath libraries, which aim to mimic GLSL, but in contrast to those GLSLmath does not focus on a complete conforming implementation of GLSL. It rather aims to provide a convenient single header file that implements the most commonly used subset of GLSL so that it is easy to use for rapid... -
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Statistics101 - Resampling Statistics
Use simulation to perform statistical analyses.
Statistics101 is an Integrated Development Environment (IDE) that uses a simple, powerful language called “Resampling Stats” to develop Monte Carlo programs to analyze and solve statistical problems. The original Resampling Stats language and computer program were developed by Dr. Julian Simon (https://www.juliansimon.com/) and Peter Bruce (https://www.scientificamerican.com/author/peter-bruce/) as a new way to teach Statistics to social science students. Of course, social science students... -
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GeoRegression
An open source Java geometry library with a focus on 2D/3D space.
Geometric Regression Library (GeoRegression) is an open source Java geometry library for scientific computing with a focus on 2D/3D space. GeoRegression provides the ability to estimate the closest point/distance between geometric primitives, best-fit shapes, and best fit geometric transform between sets of objects. It is designed for high performance and ease of use. -
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MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack
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DataMelt
Computation and Visualization environment
...DMelt 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. Linear, non-linear and symbolic regression are also available. Neural networks and various data-manipulation methods are integrated using powerful Java API. Elements of symbolic computations using Octave/Matlab scripting are supported. -
11
GenoCline
GenoCline is a free Java software for genetic cline analysis
Identification of clines from allele frequency or genome-wide databases. Angular transformation. Sigmoid function. Parameterization of a cline: orientation, Pearson’s product-moment correlation coefficient, linear and sigmoid regression and coefficient of determination. Graphical representation of the cline. Confidence limits. Spatial autocorrelation. Moran's index. Isolation by distance. Exponential regression. Correlation Fst/Distance. Centroid method. Cline's expected vs. predicted heterozygosity. MDS. Sammon projection. Geographical distances. Fst distances. ... -
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Chuck Coleman's SAS Codes
SAS Codes
...Directories under "Files" with descriptions: NESUG 2014: "A Fast, High-Precision Implementation of the Univariate One-Parameter Box-Cox Transformation Using the Golden Section Search in SAS/IML®" SESUG 2017: "Decomposing the R-squared of a Regression Using the Shapley value in SAS®" SESUG 2019: "Conditionally Executing Data Steps and Statements Based on the Presence of Variables in a SAS® Dataset" GASP 2020: "Online Winsorization of the Survey of Construction’s Price Estimates" My SESUG 2015 materials can also be found in my project "constrainingarrays" at https://sourceforge.net/projects/constrainingarrays/. -
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Open Source Data Quality and Profiling
World's first open source data quality & data preparation project
This project is dedicated to open source data quality and data preparation solutions. Data Quality includes profiling, filtering, governance, similarity check, data enrichment alteration, real time alerting, basket analysis, bubble chart Warehouse validation, single customer view etc. defined by Strategy. This tool is developing high performance integrated data management platform which will seamlessly do Data Integration, Data Profiling, Data Quality, Data Preparation, Dummy Data... -
14
NUT Nutrition Software
nutrition software to record and analyze what you eat
nut is nutrition software to record what you eat and analyze your meals for nutrient composition. The emphasis is on personal dietary experimentation to determine the best possible diet. The software uses SQLite for a portable, os-independent application. -
15
BigDecimal
Arithmetic and calculus with decimal numbers of arbitrary precision.
BigDecimal is a C # library that uses System.Numerics.BigInteger in its implementation, adding only a decimal place quantizer. In BigDecimal all the arithmetic operations are implemented, including, logarithms, systems resolution of linear equations, trigonometric functions, polynomial regression, hyperbolic functions, the notorious gamma function (factorial for non-integer real numbers) and more that will be implemented still. My intention is, at a minimum, to implement all the mathematical functions of the Windows calculator, and at most, if any, all the mathematical functions of Office Excel. -
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This application allow user to predict dissolution profile of solid dispersion systems based on algorithms like symbolic regression, deep neural networks, random forests or generalized boosted models. Those techniques can be combined to create expert system. Application was created as a part of project K/DSC/004290 subsidy for young researchers from Polish Ministry of Higher Education.
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...The former Matlab toolbox Gait-CAD was designed for the visualization and analysis of time series and features with a special focus to data mining problems including classification, regression, and clustering.
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JStats
JStats is a Java application/applet for statistical testing.
...The following tests are supported: * Parametric tests: T-test, ANOVA, Repeated Measures ANOVA * Non-parametric tests: Wilcoxon Rank-Sum, Wilcoxon Signed-Ranks, Kruskal-Wallis, Friedman * Check if datasets are normally distributed: Jarque-Bera, Shapiro-Wilk * Check if datasets have equal variances: F-test, Bartlett's test, John, Nagao and Sugiura's test * Correlation: Correlation coefficient, Spearman Rank correlation, linear regression * Confidence intervals test * Outliers: Generalized Extreme Studentized (ESD) test, outliers in ANOVA The latest version is available as applet on http://aiguy.org/Statistics.html -
19
nccmp
Compare two NetCDF files in-place.
...(gitlab.com/remikz/nccmp) Compares two NetCDF files in-place to find specific variables, dimensions and/or attributes that differ. Highly recommended for any test-driven environment and regression testing large datasets. -
20
riboshape
Predicting ribosome footprint profile shapes from transcript sequences
Riboshape is a suite of algorithms to predict ribosome footprint profile shapes from transcript sequences. It applies kernel smoothing to codon sequences to build predictive features, and uses these features to builds a sparse regression model to predict the ribosome footprint profile shapes. Reference: Liu, T.-Y. and Song, Y.S. Prediction of ribosome footprint profile shapes from transcript sequences. Proceedings of ISMB 2016, Bioinformatics, Vol. 32 No. 12 (2016) i183-i191. -
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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. It is written in C++. -
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SCaVis
Scientific Computation and Visualization Environment
...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. Linear, non-linear and symbolic regression are also available. Elements of symbolic computations using Octave/Matlab scripting are supported. The project was migrated to DataMelt. -
23
Darcy
Software for distance cartogram creation
Darcy is a software for distance cartogram creation based on Waldo Tobler bidimensional regression. -
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GPS Interactive Time Series Analysis
A software for processing and analyzing time series in Earth Science
Along with calculating basic statistics and quality parameters such as mean and variance, the soft-ware is capable of importing and visualizing different standard time series formats, determining and removing jumps and outliers, and makes numerical and publication quality graphical outputs. Bivariate statistical analysis (including correlation coefficient and linear regression) and time series analysis (including auto and cross-spectral analysis, wavelet power spectrum, spectrogram and periodicities) form the main analysis features of the software. -
25
LWPR
Locally Weighted Projection Regression (LWPR)
Locally Weighted Projection Regression (LWPR) is a fully incremental, online algorithm for non-linear function approximation in high dimensional spaces, capable of handling redundant and irrelevant input dimensions. At its core, it uses locally linear models, spanned by a small number of univariate regressions in selected directions in input space. A locally weighted variant of Partial Least Squares (PLS) is employed for doing the dimensionality reduction.
