Search Results for "python time series analysis" - Page 4

Windows application for data mining with self-organizing neural networks. It works with text data files and has convenient user interface. Is solves data mining tasks of class Recognition, continuous value Prediction, and time series Forecast.

The JTimeSeries has moved to github Please go to https://github.com/JTimeSeries/jtimeseries The SourceForge copy has not been maintained since Sep 2012 A java library to assist with capturing and storing timeseries data/metrics. Provides facilities to publish timeseries data across a network, a lightweight server to persist series data, and client user interface components for real time visualization

A Python function library to extract EEG feature from EEG time series in standard Python and numpy data structure. Features include classical spectral analysis, entropies, fractal dimensions, DFA, inter-channel synchrony and order, etc.

The scikits.timeseries python module provides classes and functions for manipulating, reporting, and plotting time series of various frequencies. The focus is on convenient data access while leveraging the existing functionality in numpy.

JMulTi is an interactive software designed for univariate and multivariate time series analysis. It has a Java graphical user interface that uses an external engine for statistical computations. It uses the framework JStatCom.

JMulTiR is an econometrics package designed for univariate and multivariate time series analysis. The numerical computations and graphics are done in R (www.r-project.org), the GUI is programmed in Java Swing with the jstatcom framework.

Breeze a multiple class model neural network development system. Network models include multi-threaded Backpropagation and Radial Basis Function Networks, for time series prediction.

Nonlinear quantitative time series analysis toolkit, written in C++ template programming style.

AGTK is a suite of software components for building tools for annotating linguistic signals, time-series data which documents any kind of linguistic behavior (e.g. audio, video). The internal data structures are based on annotation graphs.

HidroSIG is a GIS that supports raster and vectorial maps with modules oriented to the hydrological analysis, time series, remote sensing and more. It has been made 100% in java using VisAD for data visualization and using MySQL to storage all data.

To develop a software package for time series manipulation and cycles analysis. Cycles means repeated occurrences at nearly equal time intervals in any time series data. See http://www.cyclesresearchinstitute.org/ for a site about cycles.

Space Time Analysis of Regional Systems: Combines a suite of geocomputational and dynamic visualization modules for the exploratory analysis of data measured for spatial and temporal units.

SciGraphica is a scientific data visualization and analysis application, supplying many of the basic plotting features for 2D and 3D charts. It features opening several worksheets and plots to work with at the same time and PS output.

La P.A.P.A. (Python Alternative for Programming Astrophysics) want to give an alternative to the astrophysicists (and any one that use RSI-IDL) for start programming in Python using similar functions as IDL and at the same time learn the power of Python.

JTSA is an educational time series analysis tool for simple calculations and forecasts using the additional or multiplicative seasonal decomposition method.

Real-time data visualization. Graphically view your data as it's being generated. Peakster is a very intuitive GUI written entirely in Python, which monitors data at regular intervals and uses gnuplot to render 2D, 3D and superimposed plots.

Data Mining in Time Series

XMAS supports a new kind of “sit forward” time series microarray analysis through visual interaction and interoperable operators. Domain knowledge is integrated directly into the system to aid users in their analysis.

Data Mining Platform is a platform for data mining and analysis. It contains many of the new and sophisticated methods such as kernel-based classification, two-way clustering, bayesian networks, pattern recognition for time series analysis and many other