Network analysis and machine learning of relational data.
This is a loose collection of code related with learning and teaching methods for network analysis and machine learning of relational data (network data).
This code is intended for educational purposes to illustrate how methods could be implemented. It is not intended to ever become something resembling a library. If ever there is a tradeoff between a simpler and more transparent implementation on one hand and a more robust, more efficient, but more complex implementation on the other hand, we typically choose the simpler one.
All material in this repository is distributed under the GNU General Public License v3.0.
Contact: Jürgen Lerner (juergen.lerner@gmail.com)
Illustration how to implement in java efficient data structures for sparse graphs which are asymptotically optimal in both space (memory) consumption and runtime complexity of typical graph operations.
See src/kn/uni/nl/ds/graph/ for code.