- Perceptron models a neuron
- n inputs are received by it that correspond to features
- It takes the inputs and sums them, then produces an output after checking the result
- Its main use is to classify groups that are linearly separable
- It is often used for binary classification
Components
- It is composed of a summation processor, and activation function (does the thresholding) and weights.
- It takes a weighted sum of the inputs and outputs
- e.g. 1 if the sum is greater than the threshold and 0 if it isn't
- Usually the input and output weights are real numbers
- Perceptron can also have an input called the bias
- Bias allows the transfer function curve to be shifted horizontally along the input axis while the curve is left unaltered.
- Weight determines the slope
- e.g. in the eq. y = mx + b, m is the weight and b is the bias
- Activation Function
- Also know as transfer function
- It translates input signals into output signals
- The output is produced using a threshold
- The 4 types of activation functions most commonly used are: Unit step, sigmoid, piecewise linear, and Gaussian
- The unit step is a simple threshold where the output is 1 of 2 levels and it depends on whether the input is greater than or less than the threshold value
- The sigmoid contains 2 functions: tangential and logistic. Values of tangential functions are from -1 to 1 and the values of logistic functions are from 0 to 1.
- In the piecewise linear function the output arrived at from being proportional to the total weighted output.
- The Gaussian functions are continuous bell shaped curved functions. The node output which is high or low is interpreted from class membership which is 1 or 0, and depends on how close the net input is to a chosen value or average.
- Learning Rate
- Used when updating the weights and bias to get a smaller error
- Helps control how much the weights and bias are changed
- Learning In Perceptrons
- when trying to find a line to separate two classes or groups it responds to the input vectors with a target value of 0 or 1
- If the classes can be separated the solution will be found in a finite amount of time.
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