Content deleted Content added
→Summation layer: Changed title from Pattern to summation to reflect common nomenclature |
→Pattern layer: Changed Hidden to Pattern to reflect current nomenclature |
||
Line 9:
Each neuron in the input layer represents a predictor variable. In categorical variables, ''N-1'' neurons are used when there are ''N'' number of categories. It standardizes the range of the values by subtracting the median and dividing by the interquartile range.Then the input neurons feed the values to each of the neurons in the hidden layer.
===
This layer contains one neuron for each case in the training data set. It stores the values of the predictor variables for the case along with the target value. a hidden neuron computes the Euclidean distance of the test case from the neuron’s center point and then applies the RBF kernel function using the sigma values.
| |||