Scalable k-means software and test Datasets This package (a Unix tar file, gzipped) contains the source code for the software that was used to run the experiments for the article
MS-Clustering is designed to rapidly cluster large MS/MS Datasets. The program merges similar spectra (having similar m/z values ?within a given tolerance), and creates a single consensus spectrum as a representative. The input formats accepted are: dta, mgf, mzXML. The output format is mgf.
決策樹算法C4.5源碼,
The directory Data contains some sample Datasets. Many interesting data
collections are maintained by the University of California, Irvine, in a
data repository
Introduction to GPS ToolKit Pro 1.0
GPS ToolKit Pro is an ActiveX object that makes it easy to add GPS support to any Visual Basic, Visual C++, Delphi, Excel, or scripting project that supports ActiveX controls. GPS data (including lat/lon, speed, course, altitude, and dozens of other Datasets) can be accessed through GPS ToolKit s properties, and GPS ToolKit s multithreaded event-based architecture notifies your application when data has been updated, saving you from having to write messy polling routines.
％ Atomizer Main Directory, Version .802
里面信號含有分解去噪合成過程的代碼
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％ This is the main directory of the Atomizer package the full package
％ contains over 100 files, consisting of .m files, .mex files, and Datasets.
New training algorithm for linear classification SVMs that can be much faster than SVMlight for large Datasets. It also lets you direcly optimize multivariate performance measures like F1-Score, ROC-Area, and the Precision/Recall Break-Even Point.
JLAB is a set of Matlab functions I have written or co-written over the past fifteen years for the purpose of analyzing data. It consists of four hundred m-files spanning thirty thousand lines of code. JLAB includes functions ranging in complexity from one-line aliases to high-level algorithms for certain specialized tasks. These have been collected together and made publicly available for you to use, modify, and --- subject to certain very reasonable constraints --- to redistribute.
Some of the highlights are: a suite of functions for the rapid manipulation of multi-component, potentially multi-dimensional Datasets a systematic way of dealing with Datasets having components of non-uniform length tools for fine-tuning figures using compact, straightforward statements and specialized functions for spectral and time / frequency analysis, including advanced wavelet algorithms developed by myself and collaborators.
