Search Results for "regression" - Page 4
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Showing 95 open source projects for "regression"
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Lihang
Statistical learning methods (2nd edition) [Li Hang]
...The repository aims to help readers understand the theoretical foundations of machine learning algorithms through practical implementations and detailed explanations. It includes notebooks and scripts that demonstrate how key algorithms such as perceptrons, decision trees, logistic regression, support vector machines, and hidden Markov models work in practice. In addition to code examples, the project contains supplementary materials such as formula references, glossaries of technical terms, and documentation explaining mathematical notation used throughout the algorithms. The repository also provides links to related research papers and references that expand on the theoretical background presented in the book. -
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Hawaii
Wayland/QtQuick based OS with incremental updates and bundles
Hawaii is a desktop operating system built on the GNU/Linux stack with a new lightweight and fast Wayland desktop environment written with QtQuick and deeply integrated with systemd. Hawaii delivers incremental and atomic updates which gives users to ability to rollback the whole system to a known good state if a regression happens. -
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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. -
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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. -
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cpR Chemical Pathology interface for R
A graphical user interface to R for use in Clinical Chemistry
This project is a graphical user interface to the R statistical programming language designed for use in Clinical Chemistry. It allows the user to perform Passing Bablok, Deming and Linear Regression and to produce high quality images in any file format for publication. The front end is written in Python 3.3 and PyQt4 and the form was designed using Qt4 Designer. The statistical analysis is written in R. The compiled binary was made with cx_freeze. This software is free and open-source. It is released under the GNU Public license and comes with absolutely no warranty. -
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Regression Suite
Test suite with unit regrssion and execution statistics
RegressionSuite is a software test suite that incorporates measurement of the startup lag, measurement of accurate execution times, generating execution statistics, customized input distributions, and processable regression specific details as part of the regular unit tests. Essentially, RegressionSuite provides the frame-work around which the individual unit regressors are invoked (and details and statistics collected). Unit regressors are grouped into named regressor sets (or modules), and regressors are created by implementing specific regressor interfaces. ... -
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FineSplice
Enhanced splice junction detection and estimation from RNA-Seq data
...Following alignment with TopHat2 using known transcript annotations, FineSplice takes as input the resulting BAM file and outputs a confident set of expressed splice junctions with the corresponding read counts. Potential false positives arising from spurious alignments are filtered out via a semi-supervised anomaly detection strategy based on logistic regression. Multiple mapping reads with a unique location after filtering are rescued and reallocated to the most reliable candidate location. FineSplice requires Python 2.x (>= 2.6) with the following modules installed: pysam (http://code.google.com/p/pysam/) and scikit-learn (http://scikit-learn.org/). For further details check out our publication: Nucl. ... -
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math toolkit
A C++ and Python library for finance, statistics and linear algebra.
...Finance features include compound rate present/future value, annuity, various present/future value coefficients ... Statistics features include mean, median, variance, standard deviation, covariance, correlation, linear regression, probabilities and random variates of various distributions ... Linear algebra features include matrix arithmetic, inverse, determinant, rank, linear system solution, lu/qr decomposition, svd, eigen values/vectors ... And some auxiliary features like random number generators, equation solution, numerical integration, permutation/combination and gcd/lcm etc. ... -
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Provide a reference implementation of Moving Taylor Bayesian Regression, a method for nonparametric multi-dimensional function estimation with correlated errors from finite samples, as a Python package based on SciPy
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Stanford Machine Learning Course
machine learning course programming exercise
The Stanford Machine Learning Course Exercises repository contains programming assignments from the well-known Stanford Machine Learning online course. It includes implementations of a variety of fundamental algorithms using Python and MATLAB/Octave. The repository covers a broad set of topics such as linear regression, logistic regression, neural networks, clustering, support vector machines, and recommender systems. Each folder corresponds to a specific algorithm or concept, making it easy for learners to navigate and practice. The exercises serve as practical, hands-on reinforcement of theoretical concepts taught in the course. This collection is valuable for students and practitioners who want to strengthen their skills in machine learning through coding exercises. -
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mlpy
Machine Learning Python
mlpy is a Python module for Machine Learning built on top of NumPy/SciPy and of GSL. mlpy provides high-level functions and classes allowing, with few lines of code, the design of rich workflows for classification, regression, clustering and feature selection. mlpy is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License version 3. mlpy is available both for Python >=2.6 and Python 3.X. -
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pygpr is a collection of algorithms that can be used to perform Gaussian process regression and global optimization.
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A GUI application permits you to solve more than 25 types of operations including vector product,regression,correlation,equation solve,permutation,combination,factorial,mean,mode,quartiles, median, moments & more. Try it!
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Sadly JFCUnit is no longer supported but idea is neat and with a few more improvements it can be even more useful tool for regression testing. JFCUnit-2 will have distributed testing, SWT support, JUnit independent and lots of other improvements.
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Python Regression Tester - A framework for automated regression hunts to determine which changeset introduced a given problem.
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pystats is a comprehensive Python module implementing algorithms for statistics and information theory, including probability distributions, descriptive statistics, analysis of variance, regression, and inference.
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Tim Peters' FixedPoint.py + Write docs for the Library Reference manual. I expect the existing module docstring will be a good start. + Create a test driver for Python's regression suite. + Have fun modernizing it, if you like (for example,
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A set of scripts, based around doctest, for performing regression testing & code coverage analysis on Python modules.
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ExoPlanet
GUI based toolkit for running common Machine Learning algorithms.
ExoPlanet provides a graphical interface for the construction, evaluation and application of a Machine Learning model in predictive analysis. With the back-end built using the numpy and scikit-learn libraries, as a toolkit, ExoPlanet couples fast and well tested algorithms, a UI designed over the Qt4 framework, and graphs rendered using Matplotlib to provide the user with a rich interface, rapid analytics and interactive visuals. ExoPlanet is designed to have a minimal learning curve,...
