Man pages for TeachNet
Fits Neural Networks to Learn About Backpropagation

accuracy.meComputes accuracy
computeGrad1Computes a gradient
computeGrad2Computes a gradient
computeOutput1Computes output
computeOutput2Computes output
confusionComputes confusion matrix
createWeights1Creates random weights
createWeights2Creates random weights
crossEntropyCross entropy
find.ThresholdFinds best threshold
fitTeachNet1One step in backpropagation
fitTeachNet2One step in backpropagation
is.acctChecks for correct input
is.dataChecks for correct input
is.decayChecks for correct input
is.errChecks for correct input
is.learnChecks for correct input
is.numberOfNeuronsChecks for correct input
is.sampleChecks for correct input
is.sampleLengChecks for correct input
is.stepMaxChecks for correct input
is.thres.errorChecks for correct input
logisticLogistic function
logistic.differentialDifferential of logistic function
predict_WeightsComputes prediction
predict_Weights2Computes prediction
squaredErrorComputes squared error
sumCrossEntropySums up cross entropy
sumSquaredErrorSums up squared error
TeachNetFits the neural network
TeachNet-packageFit neural networks with up to 2 hidden layers and one output...
transformPredictionTransforms prediction
Weights2-classWeights2 objects
Weights-classWeights objects
TeachNet documentation built on May 2, 2019, 7 a.m.