LTF-C (Local Transfer Function Classifier) is an artificial neural network solving classification problems. It has similar architecture as Radial Basis Function (RBF) neural network, but utilizes entirely different training algorithm.
LTF-C performs very well in difficult real-world problems, like: handwritten digit recognition, credit risk assessment or classification of breast cancer tissue.
To learn more about LTF-C, see:
- Paper with detailed description of LTF-C (ps.zip 190K or pdf.zip 150K]
- Report (ps.zip or pdf.zip) and PowerPoint presentation for the 2nd EUNITE Competition - details of application of LTF-C to Modeling the Bank's Client Behavior (LTF-C won this competition!)
- PowerPoint presentation of LTF-C (in Polish)
- LTF-Cimulator - Windows application for simulating LTF-C