Hi
Thanks for your reply. I have compared my data with some other which works and I cannot see the difference...
The structure of my data is shown below:
drug param1 param2 param3 param4 param5 Class
A : 1 Min. :111.0 Min. : 2.0 Min. : 75.0 Min. :-20.00 Min. :-60.000 Min. :1.000
B : 1 1st Qu.:253.5 1st Qu.:15.0 1st Qu.:132.5 1st Qu.: 12.00 1st Qu.: 0.000 1st Qu.:1.000
C : 1 Median :335.0 Median :28.0 Median :164.0 Median : 40.00 Median : 6.000 Median :2.000
D : 1 Mean :383.0 Mean :33.0 Mean :166.0 Mean : 35.26 Mean : 4.447 Mean :1.895
E : 1 3rd Qu.:433.5 3rd Qu.:42.5 3rd Qu.:200.5 3rd Qu.: 54.00 3rd Qu.: 20.500 3rd Qu.:2.000
F : 1 Max. :863.0 Max. :93.0 Max. :280.0 Max. : 89.00 Max. : 45.000 Max. :3.000
(Other):13
The structure of the example data which worked is shown below:
education age parity induced case spontaneous stratum pooled.stratum
0-5yrs : 12 Min. :21.00 Min. :1.000 Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. : 1.00 Min. : 1.00
6-11yrs:120 1st Qu.:28.00 1st Qu.:1.000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:21.00 1st Qu.:19.00
12+ yrs:116 Median :31.00 Median :2.000 Median :0.0000 Median :0.0000 Median :0.0000 Median :42.00 Median :36.00
Mean :31.50 Mean :2.093 Mean :0.5726 Mean :0.3347 Mean :0.5766 Mean :41.87 Mean :33.58
3rd Qu.:35.25 3rd Qu.:3.000 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:62.25 3rd Qu.:48.25
Max. :44.00 Max. :6.000 Max. :2.0000 Max. :1.0000 Max. :2.0000 Max. :83.00 Max. :63.00
So still not sure how to solve the problem ....
_________
From: PIKAL Petr [petr.pikal at precheza.cz]
Sent: 13 December 2012 07:16
To: dada; r-help at r-project.org
Subject: RE: [R] neural net
Hi
-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
project.org] On Behalf Of dada
Sent: Thursday, December 13, 2012 12:41 AM
To: r-help at r-project.org
Subject: [R] neural net
Hi
I would like to do neural netowrk analysis on my data. It look like
this:
drug param1 param2 param3 param4 param5 class
A 111 15 125 40 0.5 1
B 347 13 280 55 3 2
C 335 9 119 89 -40 1
D 477 37 75 2 0 1
E 863 24 180 10 5 2
F 737 28 150 15 6 2
G 390 63 167 12 0 3
H 209 93 200 48 45 3
I 376 72 201 45 -60 3
J 262 16 205 49 25 3
K 273 39 267 53 11 1
L 192 33 164 19 15 2
M 282 2 213 86 30 1
N 111 11 198 68 -21 1
O 387 20 143 12 16 2
P 674 15 78 -20 -17 2
R 734 54 140 24 7 2
S 272 46 159 57 28 2
T 245 37 90 6 31 2
I have entered the code below:
nn <- neuralnet(
+ class~param1+param2+param3+param4+param5+param5,
+ data=mydata, hidden=2, err.fct="ce",
+ linear.output=FALSE)
However the error appeared:
Error in model.frame.default(formula.reverse, data) :
object is not a matrix
I changed the data frame to matrix:
mydata.mat=as.matrix(mydata)
This is not very wise. It changes all numeric values to character. From documentation and your data frame there is nothing obviously wrong. However you did not provide info about structure of your data something like
summary(mydata) or str(mydata).
Documentation does not say much about how neuralnet reacts e.g. on NA values. The best way how to proceed seems to try recommended data and compare them to your data to see where are the differences.
Or you can read sources to see where the error message originates.
Regards
Petr
but still the same error appears...
How can I fix this ? I would be very grateful for your help !
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