Monotonicity Hints

: Neural networks are competitive tools for classification problems. In this context, a hint is any piece of prior side information about the classification. Common examples are monotonicity hints. The present paper focuses on learning vector quantization neural networks and gives a simple, however effective, technique, which guarantees that the predictions of the network obey the required monotonicity properties in a strict fashion. The method is based on a proper modification of the Euclidean distance between input and codebook vectors.

• Type: Conference
• Year: 1996
• Where: NIPS
• Authors: Joseph Sill, Yaser S. Abu-Mostafa
• Keywords: Neural Networks, NIPS 1996, NIPS 2007, Quantization Neural Networks, Required Monotonicity Properties