Search Results for "regression"

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...

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++.

Handwritten Signature SDK supports: dynamic time wrapping (DTW), extended regression (ER), signature sampling, direction hash and features extraction: see wiki for more info.

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

...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.

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

GMM-GMR is a light package of functions in C/C++ to compute Gaussian Mixture Model (GMM) and Gaussian Mixture Regression (GMR). It allows to encode any dataset in a GMM, and GMR can then be used to retrieve partial data by specifying the desired inputs.

pystats is a comprehensive Python module implementing algorithms for statistics and information theory, including probability distributions, descriptive statistics, analysis of variance, regression, and inference.

Probe Deeper PHP will provide class libraries for simple and advanced statistical analyses, including multiple regression, forecasting, hypotheses testing, etc.