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 |
is.acct | Checks for correct input |
is.data | Checks for correct input |
is.decay | Checks for correct input |
is.err | Checks for correct input |
is.learn | Checks for correct input |
is.numberOfNeurons | Checks for correct input |
is.sample | Checks for correct input |
is.sampleLeng | Checks for correct input |
is.stepMax | Checks for correct input |
is.thres.error | Checks for correct input |
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 |
TeachNet-package | Fit neural networks with up to 2 hidden layers and one output... |
transformPrediction | Transforms prediction |
Weights2-class | Weights2 objects |
Weights-class | Weights objects |
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