Search Results for "regression" - Page 12
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Showing 358 open source projects for "regression"
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TMVA Toolkit for Multi Variate Analysis
A ROOT-integrated toolkit for multivariate analysis
TMVA is a ROOT-integrated toolkit for multivariate classification and regression analysis. TMVA performs the training, testing and performance evaluation of a large variety of multivariate methods. Since 2013, TMVA has been fully integrated with ROOT and is distributed as part of it. The new homepage of TMVA is https://root.cern -
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SAS macros and sample code for stratifying (and aggregating) data according to time-varying covariates. Especially useful for Poisson regression, Cox regression and calculating standardised incidence ratios.
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DNAcompact
Genome compression algorithm with/without reference (Linux/Windows)
As the technique of acquiring genome sequences advances, the storage and data transferring of large genome data are becoming important concerns for biomedical researchers. We propose a two pass genome compression algorithm, which highlights the synthesis of complementary contextual models and the introduction of logistic regression mixture method, to improve the compression performance. The proposed framework handles genome compression with and without reference seque- nces, and demonstrated performance advantage over the best existing algorithms. The proposed method without a reference led to bit rates of 1.720 and 1.838 bits per base for bacteria and yeast, which are approximately 3.7% and 2.6% better than the state-of-the-art algorithm. ... -
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HSOC
Heterogeneous System-on-Chip Platform
HSoC is a open source, SystemC-based, cycle-accurate virtual platform for heterogeneous shared memory-based multicore SoCs. Each HSoC component has a clean interface, implements a separate class, and includes regression tests. Large-scale models can be instantiated, by connecting objects from all HSoC libraries. Each object may collect data by invoking a monitoring library. The target users are CS/EE professionals. Some experience with SoC design methodology and SystemC (e.g. reading the SystemC user manual and/or running the examples) is required. ... -
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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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SysLinea
Linear Systems; Linear Regression; Non Linear Regression
Solves Linear Systems From a table it gives the function for Linear and Non Linear Regression. Precompiled for Linux and Windows. No instalations, just unpack (.zip) and click on the executable, can be run from a memory stick. ATENTION! On linux, sometimes the copy is not settled right, try to right click -> properties -> allow to be executed as a program. It is not compiling in my new installation of Lazarus. -
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Firefly's Beetroot
Regression testing simplified.
Firefly's Beetroot is a regression tester designed with ease of use in mind. The only requirement to operate it is some basic knowledge of the UNIX shell. Note that this is not a unit test framework. Testing occurs at program granularity, not at a level of a function. This is meant to be used only with software with a stable user interface. Changes in the interface could break your tests. -
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Weibull-based reliability toolkit for R
R package for Weibull analysis on (life-)time observations.
This is a small R package for doing Weibull-based reliability analysis. This R package is now obsolete and has been superseded by 'project Abernethy' on http://r-forge.r-project.org/projects/abernethy/. -
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r4st
A database rapid application development tool
...It uses shell scripts to drop/add Postgresql database tables/views with data loaded from sql and csv files. This process allows users to apply changes then re-build the system. It is essentially a customizable database regression system. The base schema and data module represent a plant database intended for educational and scientific usage. -
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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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This project aims to provide a linux kernel regression test framework which will provide a systematic way to find a regression of the Linux Kernel.
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Stochastic gradient boosting
A java implementation of the stochastic gradient boosting method
...The method can be applied to either categorical data or quantitative data. The current Java implementation uses the L2 norm loss function, which is suitable for the general regression task. -
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pscbreg
Pitzer-Simonson-Clegg Model Binary System Regression
This program is developed for regressing the binary parameters of primitive Pitzer-Simonson-Clegg model (1992a, 1992b). The defult relationship of binary parameter and temperature is as P = a + b * T. -
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TPPS is a toolkit to make parallelized parameter scans of TMVA methods (regression and classification) using a batch system like LSF Batch. It is intended to be very simple, such that the user can easily modify it and dapt it to his or her needs.
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Statistical models with python using numpy and scipy. Currently covers linear regression (with ordinary, generalized and weighted least squares), robust linear regression, and generalized linear model, discrete models, time series analysis and other statistical methods.
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...MTL was used to build a 3d Scanner. MTL consists of pars B - Basic Functions, Matrices, Images, Hypermodels (3d Models and up) N - Numeric Functions ranging from linear regression over nonlinear optimization to singular-value computation I - Image filters and Image enhancement H - Hardware related (optional part), does require additional libraries and is only useful on certain hosts. G - Hyper-Model functions such as ray-plane intersections etc.
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Linear Regression
linear regression along with plotting
Linear regression with plotting facility for simple and 2d regression. linear_regression.c is the main file and Include the library lib_sim_eq.c. You must have installed gnuplot prior to compiling the program. -
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TestNGEE
Run TestNG tests inside servlet container. Great for integration tests
...By running your tests inside the target JEE container (instead of emulating the container resources), you will test the real thing. During our projects, we already detected problems during regression tests caused by a fix that was applied to our Websphere Application Server (in one version the classloader worked in one way, them it changed!). For using it, create a web project and copy the contents from our sample war to it. Put all your annotated TestNG tests inside the same project (/WEB-INF/classes) and call http://host/yourcontext/TestServlet. ... -
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Trophix
prediction of HIV-1 tropism
Program for predicting HIV-1 coreceptor usage using logistic regression: input is a HIV-1 genotypic sequence spanning the V3 loop of the envelope region. -
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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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Nen
neural network implementation in java
3-layer neural network for regression and classification with sigmoid activation function and command line interface similar to LibSVM. Quick Start: "java -jar nen.jar" -
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GP System in C/C++
GP System in C/C++
This is a very elementary GP system written in C/C++ of symbolic regression,The input to the program is the file containing Terminal set. -
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ProteinLasso
ProteinLasso: A Lasso regression approach to protein inference problem
ProteinLasso: In this paper, we formulate the protein inference problem as a constrained Lasso regression problem and then solve it with a fast pathwise coordinate descent algorithm. The new inference algorithm ProteinLasso explores an ensemble learning strategy to address the sparsity parameter selection problem in Lasso model. ProteinLasso is implemented in Java and can run on any Java Virtual Machine (JVM) regardless of computer architecture. -
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XPect allows test developers to describe regression tests for message oriented systems in XML. XPect leans on JUnit and XPect test should be kicked off as JUnit TestSuites.
