CODEWITHSUNDEEP
rmodeling
Dhruv Rana
Dhruv Rana

Reputation: 11

How to make predictions after every 50 cycles in RSNNS

I am RSNNS to make a model. I am using QuickProp algorithm. here's my neural network:

mydata1 <- read.csv("-1-5_rand1.csv");
mydata <- mydata1[1:151, ]
test_set <- mydata1[152:168, ]
test_set1 <- test_set[c(-7)]
a <- SnnsRObjectFactory()
input <- mydata[c(-7)]
output <- mydata[c(7)]
b <- splitForTrainingAndTest(input, output, ratio = 0.22)
a <- mlp(b$inputsTrain, b$targetsTrain, size = 9, maxit = 650, learnFunc = "Quickprop", learnFuncParams = c(0.01, 2.5, 0.0001, 0, 0), updateFunc = "Topological_Order",
     updateFuncParams = c(0.0), hiddenActFunc = "Act_TanH", computeError=TRUE, initFunc = "Randomize_Weights", initFuncParams = c(-1,1),
     shufflePatterns = TRUE, linOut = FALSE, inputsTest = b$inputsTest, targetsTest = b$targetsTest)

I am predicting using test set as:

predictions <- predict(a, test_set1)

Is it possible to in RSNNS to predict after every 50 cycles using test set instead of predicting after 650 cycles?

Upvotes: 1

Views: 131

Answers (1)

Christoph Bergmeir
Christoph Bergmeir

Reputation: 111

the answer is you can't do it with the high-level interface, but with the low-level interface, you can have a look, e.g., at the mlp_irisSnnsR.R demo that is included in RSNNS

Upvotes: 3

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