TeachNet-package |
Fit neural networks with up to 2 hidden layers and one output neuron |
*-method |
Weights objects |
*-method |
Weights2 objects |
+-method |
Weights objects |
+-method |
Weights2 objects |
--method |
Weights objects |
--method |
Weights2 objects |
accuracy.me |
Computes accuracy |
computeGrad1 |
Computes a gradient |
computeGrad2 |
Computes a gradient |
computeOutput1 |
Computes output |
computeOutput2 |
Computes output |
confusion |
Computes confusion matrix |
createWeights1 |
Creates random weights |
createWeights2 |
Creates random weights |
crossEntropy |
Cross entropy |
find.Threshold |
Finds best threshold |
fitTeachNet1 |
One step in backpropagation |
fitTeachNet2 |
One step in backpropagation |
logistic |
Logistic function |
logistic.differential |
Differential of logistic function |
predict.Weights |
Computes prediction |
predict.Weights2 |
Computes prediction |
squaredError |
Computes squared error |
sumCrossEntropy |
Sums up cross entropy |
sumSquaredError |
Sums up squared error |
TeachNet |
Fits the neural network |
transformPrediction |
Transforms prediction |
Weights-class |
Weights objects |
Weights2-class |
Weights2 objects |