Here is the code that i had used:
#########################################
## Read in the raw data
fitness <- c(44,89.47,44.609,11.37,62,178,182,
40,75.07,45.313,10.07,62,185,185,
44,85.84,54.297,8.65,45,156,168,
42,68.15,59.571,8.17,40,166,172,
38,89.02,49.874,9.22,55,178,180,
47,77.45,44.811,11.63,58,176,176,
40,75.98,45.681,11.95,70,176,180,
43,81.19,49.091,10.85,64,162,170,
44,81.42,39.442,13.08,63,174,176,
38,81.87,60.055,8.63,48,170,186,
44,73.03,50.541,10.13,45,168,168,
45,87.66,37.388,14.03,56,186,192,
45,66.45,44.754,11.12,51,176,176,
47,79.15,47.273,10.6,47,162,164,
54,83.12,51.855,10.33,50,166,170,
49,81.42,49.156,8.95,44,180,185,
51,69.63,40.836,10.95,57,168,172,
51,77.91,46.672,10,48,162,168,
48,91.63,46.774,10.25,48,162,164,
49,73.37,50.388,10.08,67,168,168,
57,73.37,39.407,12.63,58,174,176,
54,79.38,46.08,11.17,62,156,165,
52,76.32,45.441,9.63,48,164,166,
50,70.87,54.625,8.92,48,146,155,
51,67.25,45.118,11.08,48,172,172,
54,91.63,39.203,12.88,44,168,172,
51,73.71,45.79,10.47,59,186,188,
57,59.08,50.545,9.93,49,148,155,
49,76.32,48.673,9.4,56,186,188,
48,61.24,47.92,11.5,52,170,176,
52,82.78,47.467,10.5,53,170,172
)
fitness2 <- data.frame(matrix(fitness,nrow = 31, byrow = TRUE))
colnames(fitness2) <-
c("Age","Weight","Oxygen","RunTime","RestPulse","RunPulse","MaxPulse")
attach(fitness2)
## Create the input dataset
indep <- fitness2[,-3]
## Create the neural network structure
net.start <- newff(n.neurons=c(6,6,6,1),
learning.rate.global=1e-2,
momentum.global=0.5,
error.criterium="LMS",
Stao=NA, hidden.layer="tansig",
output.layer="purelin",
method="ADAPTgdwm")
## Train the net
result <- train(net.start, indep, Oxygen, error.criterium="LMS", report=TRUE,
show.step=100, n.shows=5 )
## Predict
pred <- sim(result$net, indep)
pred
###########################################
Here I am trying to predict Oxygen levels using the 6 independent
variables. But whenever I am trying to run a prediction - I am getting constant
values throughout (In the above example - the values of pred).
Thanks & Regards,
Indrajit
----- Original Message ----
From: Max Kuhn <mxk...@gmail.com>
To: Indrajit Sengupta <indra_cali...@yahoo.com>
Cc: markle...@verizon.net; R Help <r-help@r-project.org>
Sent: Wednesday, May 27, 2009 9:19:47 PM
Subject: Re: [R] Neural Network resource
> I fed this data into a Neural network (3 hidden layers with 6 neurons in each
> layer) and trained the network. When I passed the input dataset and tried to
> get the predictions, all the predicted values were identical! This confused
> me a bit and was wondering whether my understanding of the Neural Network was
> wrong.
>
> Have you ever faced anything like it?
You should really provide code for us to help. I would initially
suspect that you didn't use a linear function between your hidden
units and the outcomes.
Also, using 3 hidden layers and 6 units per layer is a bit much for
your data set (30-40 samples). You will probably end up overfitting.
--
Max
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