Artificial Neural Networks
- Simplest ANN
- Based upon - Linear Threashold Unit (LTU). In neurons, you give signals. In perceptron you give numbers.
- Each connection is associated with weight
- LTU computes weighted sum of inputs
- A single LTU can be used for simple linear binary classification
- Computes linear combination of inputs, & if result is more than a threshold - it gives positive otherwise negative
- A perceptron is single layer of LTU, with each neuron connected to all inputs.
- Perceptron do not output class probalility, they just make hard prediction.
- This limitation of perceptron can be entirely eleminated by stacking multiple perceptrons
