About this document
Delta Learning Rule Algorithm by amit621988 is a document available to read on EtoBox.
The document describes two learning algorithms: 1) The delta learning rule uses a bipolar sigmoid activation function to train weights using small random initial values. It updates weights based on the error between the target and actual output, and trains until the cumulative error falls below a threshold. 2) The perceptron learning rule also initializes small random weights and trains by presenting inputs to compute output, then updating weights based on error. It iterates until the cumulative error reach
- Author
- amit621988
- Language
- EN