Search Results for "linear regression" - Page 2
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Showing 67 open source projects for "linear regression"
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lightning library
Large-scale linear classification, regression and ranking in Python
lightning is a library for large-scale linear classification, regression and ranking in Python. -
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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. ... -
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Machine-Learning
kNN, decision tree, Bayesian, logistic regression, SVM
Machine-Learning is a repository focused on practical machine learning implementations in Python, covering classic algorithms like k-Nearest Neighbors, decision trees, naive Bayes, logistic regression, support vector machines, linear and tree-based regressions, and likely corresponding code examples and documentation. It targets learners or practitioners who want to understand and implement ML algorithms from scratch or via standard libraries, gaining hands-on experience rather than relying solely on black-box frameworks. This makes the repo suitable for students, hobbyists, or developers who want to deeply understand how ML algorithms work under the hood and experiment with parameter tuning or custom data. ... -
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Bayesian machine learning notebooks
Notebooks about Bayesian methods for machine learning
Notebooks about Bayesian methods for machine learning. -
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Charlatano
Proves JVM cheats are viable on native games
...Bone trigger, reduced flash. Stream-proof OpenGL overlay with box and skeleton ESP. /Glow ESP (not stream-proof) Humanized bunny hop using scroll input. "Flat" aim bot with traditional linear-regression paths (not safe for use on leagues! use "PathAim" instead) -
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The VOLARE-CANTARE workflow is designed to help researchers find and visualize patterns in multi-omic data. VOLARE (Visualization Of LineAr Regression Elements) is a visual analysis environment designed for multi-omic biological studies. CANTARE (Consolidated Analysis of Network Topology And Regression Elements) is a workflow for building predictive regression models from network neighborhoods in multi-omic networks. VOLARE is licensed under BSD 3-Clause A manuscript providing additional details on VOLARE can be found at: https://doi.org/10.1186/s12859-019-3021-0 A hosted version of VOLARE can be found at: http://aasix.cytoanalytics.com/volare
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Zipline
Zipline, a Pythonic algorithmic trading library
Zipline is a Pythonic algorithmic trading library. It is an event-driven system for backtesting. Zipline is currently used in production as the backtesting and live-trading engine powering Quantopian -- a free, community-centered, hosted platform for building and executing trading strategies. Quantopian also offers a fully managed service for professionals that includes Zipline, Alphalens, Pyfolio, FactSet data, and more. Installing Zipline is slightly more involved than the average Python... -
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GSMLBook
Recipes for basic machine learning algorithms using sklearn in jupyter
...The emphasis is primarily on learning to use existing libraries such as Scikit-Learn with easy recipes and existing data files that can found on-line. Topics include linear, multilinear, polynomial, stepwise, lasso, ridge, and logistic regression; ROC curves and measures of binary classification; nonlinear regression (including an introduction to gradient descent); classification and regression trees; random forests; neural networks; probabilistic methods (KNN, naive Bayes', QDA, LDA); dimensionality reduction with PCA; support vector machines; and clustering with K-Means, hierarchical, and DBScan. ... -
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Machine Learning From Scratch
Bare bones NumPy implementations of machine learning models
...The goal of the project is to help learners understand how machine learning algorithms work internally by building them step by step from fundamental mathematical operations. The repository includes implementations of algorithms ranging from simple models such as linear regression and logistic regression to more complex techniques such as decision trees, support vector machines, clustering methods, and neural networks. Because the code avoids external machine learning libraries, it exposes the full logic behind model training, optimization, and prediction processes. The project also provides examples and explanations that illustrate how the algorithms behave and how different components interact during training. -
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Dive-into-DL-TensorFlow2.0
Dive into Deep Learning
This project changes the MXNet code implementation in the original book "Learning Deep Learning by Hand" to TensorFlow2 implementation. After consulting Mr. Li Mu by the tutor of archersama , the implementation of this project has been agreed by Mr. Li Mu. Original authors: Aston Zhang, Li Mu, Zachary C. Lipton, Alexander J. Smola and other community contributors. There are some differences between the Chinese and English versions of this book . This project mainly focuses on TensorFlow2... -
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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. -
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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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Retop Math Library
A Java Math Library for creating advanced programs
Regression Polynomial Regression Noise generator Advanced Matrix and Vector classes Physics Collisions Window to visualize functions -
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MOSGWA
genome wide association studies / Bayesian-type information criteria
MOSGWA is a tool for genome wide association studies (GWAS). It currently implements a search strategy using logistic regression and linear regression. -
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Win-Brash
A Windows Native Bourne Shell Interpreter
Win-Brash is a recoding, from scratch, of the Bourne shell as a native Microsoft Windows multi-threaded command line application. It uses Bourne shell syntax but recognizes Windows file names. The TAB key helps convert Unix style pathnames to fully valid windows pathnames. It also adds missing backslashes -- to reduce the need to always type two. For Documentation see: http://www.bordoon.com/brash To give brash.exe a try, use the download link to get winbrash-1.2.16.zip. Unzip... -
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BioPPSy
A biochemical property prediction system
...The program models a given property's dependence on a collection of molecular and structural descriptors using a training set of molecules. Neural networks and support vector regression are available, as well as linear models. The models generated by this analysis can then be used to predict the properties of compounds during the development of new and novel drugs. The program and its databases are all open-source. -
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Accord.NET Framework
Machine learning, computer vision, statistics and computing for .NET
The Accord.NET Framework is a .NET machine learning framework combined with audio and image processing libraries completely written in C#. It is a complete framework for building production-grade computer vision, computer audition, signal processing and statistics applications even for commercial use. A comprehensive set of sample applications provide a fast start to get up and running quickly, and extensive documentation and a wiki help fill in the details. The Accord.NET project provides... -
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L1-norm-robust-regression
linear regression on the basis of minimal absolute deviations error
This software provides a Fortran95 implemented routine to call and obtain the L1-norm regression coefficients. The "standard" linear regression minimizes the squared error. (L2-norm-regression). It allows for a simple solution process, hence its popularity. But it is not robust to outlier points. L1-norm regression is robust with respect to outliers but the solution algorithm is more difficult. It minimizes the sum of absolute deviations. -
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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 -
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SEPTA Next Bus
Prediction API for Septa buses
Use SEPTA bus gps data to ultimately determine when a bus will reach a certain stop. -
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Data visualization tool
scientific data visualization, time history, scatter plots, spectral
View/plot/graph scientific data such as time history, scatter plots, PSD, Bode, Flight track, tephigram, linear regression (single and multi variate). Playback was developed for aerospace and atmospheric research environment and as such support plotting specifically for these disciplines but it is by no means limited to these and contains many generalized plotting and data visualization capabilities. Playback uses GTK2 and compiles under Linux. -
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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
...The program is fully multiplatform (100% Java) and integrated with Java and a number of scripting languages: Jython (Python), Groovy, JRuby, BeanShell. 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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JLWR
Java Locally weighted regression (JLWR)
Locally weighted regression (LWR) is a variation of the standard linear regression technique in which training points close to the query point have more influence over the fitted regression surface. Given a set of training points, linear regression ts the linear model that minimizes squared prediction error over the whole training set. source on git :https://github.com/ahrnazemi/jlwr This implicitly assumes that we know the global form of the underlying function that generated the data. -
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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.
