Search Results for "spatial mining"

...According to our benchmark and third-party research papers, Sedona has 50% less peak memory consumption than other Spark-based geospatial data systems for large-scale in-memory query processing. Sedona offers Scala, Java, Spatial SQL, Python, and R APIs and integrates them into underlying system kernels with care. You can simply create spatial analytics and data mining applications and run them in any cloud environments.

...attredirects=0&d=1 http://sourceforge.net/projects/geoms2/files/Mining.7z/download

The SPAWNN toolkit is an innovative toolkit for spatial analysis with self-organizing neural networks which is particularily useful for spatial analysis, visualization and geographical data mining. To run the toolkit, simply download and execute (double-click) the jar-file. Please cite: - Hagenauer, J., & Helbich, M. (2016). SPAWNN: A Toolkit for SPatial Analysis With Self-Organizing Neural Networks.

Current functions: 1. The General Association Rule Mining Framework(GARMF) library, which support mining association rules from transactions(boolean, weighted, fuzzy), spatial datasets (vector and raster) and spatio-temporal datasets (raster snapshots). Besides it support incremental mining. 2. Rule Filtering Library (RFL), a library for rule evaluation. 3. Besides, DAP-Shell, a GUI shell for GARMF and RFL, will be provided.

...SubPatCNV is the implementation of a variation of approximate association pattern mining algorithm under a spatial constraint on the positional CNV probe features. The implementation scales to high-density array data with hundreds of thousands features.

...Software from this site may be used freely and revised as is useful, with the proviso that credit be given in the form of citation or link back to http://gerrylushington.users.sourceforge.net/. The latest tool deposited here (see Code directory) is designed to graphically render (in PyMol) spatial affinity trends derived from molecular docking simulations. Additional tools will be deposited here as time permits. About the developer: Gerald Lushington is a computational scientist with primary interests in chemical informatics, structural biology, drug discovery and molecular modeling. He performs fee-for-service consulting in these areas, as well as data mining and technical writing.