7 packages tagged with “datamining”
Association Mining Algorithms - Apriori
DataMining Algorithms Existing Algorithms - Apriori
TeeChart for Javascript is available as a standalone product and as an export format across the TeeChart product range. Both formats enable HTML5 live in-browser charts as a visualisation format for a selected range of TeeChart data series types. Other series types, not supported in the dynamic model, may be output to browsers as static HTML5 charts. See www.w3.org/TR/html5 for more details of the HTML5 specfication. TeeChart for Javascript Live charts support zoom and scroll, a variety of interactive mouse-click events and finger-touch sensitivity on touch devices (mobile, ipad, tablets...). TeeChart Series Types currently supported are: Bar, Horizbar, Line, SmoothLine, Pie, Donut, Area, HorizArea, SmoothArea, Point (Scatter XY), Bubble, Candle (OHLC), Volume, Gauges, Clocks, World / USA / Europe maps and Spark lines.
1. Source code can be download from github.com: https://github.com/xieguigang/sciBASIC 2. Code style guideline for VisualBasic of this runtime library at codeproject article: http://www.codeproject.com/Articles/1101608/Code-style-guidelines-for-Microsoft-VisualBasic 3. Article about manipulate these document at codeproject: http://www.codeproject.com/Articles/1099296/Easy-Document-in-VisualBasic
The Crawler-Lib Engine is a general purpose workflow enabled task processor. It has evolved from a web crawler over data mining and information retrieval. It is throughput optimized and can perform thousands of tasks per second on standard hardware. Due to its workflow capabilities it allows to structure and parallelize even complex kind of work. Please visit the project page for the complete view of the Crawler-Lib Engine. A license for the Anonymous Edition is included in the package. A license for the more powerful free Community Edition can be generated on the project page. A unrestricted license is available too.
Software for corpus linguists and text/data mining enthusiasts. The CorpusExplorer combines over 45 interactive visualizations under a user-friendly interface. Routine tasks such as text acquisition, cleaning or tagging are completely automated. The simple interface supports the use in university teaching and leads users/students to fast and substantial results. The CorpusExplorer is open for many standards (XML, CSV, JSON, R, etc.) and also offers its own software development kit (SDK).
Machine learning library for .Net and Mono. Currently has Linear Regression, Logistic Regression, Ridge Regression/Classifier, Svm classifier. Initially it is port of popular Scikit-learn machine learning python library and has very close design. Sharpkit.Learn is based on the state of the art algorithm implementations and uses liblinear, libsvm, Math.Net etc. Various BLAS providers like MKL can be used to speed up the computation. Both dense and sparse matrices are supported.