Search Results for "linear regression" - Page 3
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Showing 67 open source projects for "linear regression"
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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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miRNA Temporal Analyzer (mirnaTA)
Differential expression analysis tool for miRNAs in temporal studies
...The mirnaTA requires that users provide data from a minimum of two time points and analyze up to 20 time points. To normalize data and remove technical variability, Normal Quantile Transformation (NQT) was used, and the normalized data is analyzed using linear regression model to locate any miRNAs which are differentially expressed in a linear manner. Any miRNAs with P-value<0.05 are considered statistically significant. Remaining miRNAs which did not fit in linear model are further analyzed in two different methods: (1) if the number of time points <3, CDF of the normal distribution, and (2) if the number of time points is >= 3, ANOVA is utilized. ... -
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phcfM
R package for modelling anthropogenic deforestation
...It was named after the REDD+ pilot-project 'programme holistique de conservation des forêts à Madagascar'. phcfM includes two main functions: (i) demography(), to model the population growth with time in a hierarchical Bayesian framework using population census data and Gaussian linear mixed models and (ii) deforestation(), to model the deforestation process in a hierarchical Bayesian framework using land-cover change data and Binomial logistic regression models with variable time-intervals between land-cover observations. The two functions use embedded Gibbs samplers written in C++ with the Scythe statistical library to reduce computational time. -
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Fast Matrix for Java
General purpose matrix utilities for Java in Parallel Computing
Fast Matrix for Java (fm4j) is a general-purpose matrix utility library for computing with dense matrices. fm4j encapsulated different underlying implementations and select the optimal one in run-time depending on the size of the input matrix. Moreover, fm4j employs Java (Tm) Concurrency to take advantage of the computation power of multi-cor processors. -
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Statistics modules in Perl Data Language, with a quick-start guide for non-PDL people. They make the PDL shell work like R, but with PDL threading (fast automatic iteration) of procedures including t-test, linear regression, and k-means clustering.
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math toolkit
A C++ and Python library for finance, statistics and linear algebra.
A lightweight 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 ... ... -
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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. -
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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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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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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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Nagosion is a new Open Source Project which give you an other approch of Supervision. In fact, Nagosion allows you to create a linear regression model in order to graph your futur capacity storage needs.
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Himalaya Tools is a suite of programs focusing on new techniques in data mining. MAFIA/SPAM mine patterns from transactional databases. SECRET is a new algorithm for scalable linear regression trees. More algorithms will be added over time.
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Some user defined functions (UDFs) coded in C to enhance the functionality of the MySQL database server. With these functions it is possible to calculate median values, linear regression parameters, effective column widths etc. directly from MySQL
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Library that will supply a clean interface for Linear, Quadratic, and Logarithmic regressions including verification for autocorrelation and heteroscedasticity using Durbin Watson and White tests.
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GPTIPS
Symbolic ML and non-linear regression platform for MATLAB
See gptips.org for a full description.
