Hello everybody,
I'm trying to harness the power of neural networks for image classification of
big rasters using the `RSNNS` package in `R`.
As for the data preparation and training of the model, everything works
perfectly fine and the accuracies look quite promising.
Subsequently, I'm try
> On Mar 3, 2016, at 12:33 PM, jake88 wrote:
>
> Data set attached … rename to mydata.csv .
>
>
>
>
>
> require ( RSNNS )
> mydata = read.csv("mydata.csv",header = TRUE)
# Needed to change to mydata.txt
>
> mydata.train = mydata[3000:1,]
>
> mydata.test = mydata[10005:10006,]
>
> m
t;- elman ( mydata.train[,2:19],mydata.train[,1], size =100 ,
> learnFuncParams =c (0.1) , maxit =1000)
>
> pred <-predict (myfit , mydata.test[,2:19])
>
>
>
>
>
> From: Charles Determan [mailto:cdeterma...@gmail.com]
> Sent: Thursday, M
;-predict (myfit , mydata.test[,2:19])
From: Charles Determan [mailto:cdeterma...@gmail.com]
Sent: Thursday, March 03, 2016 6:31 AM
To: jake88
Cc: r-help
Subject: Re: [R] RSNNS neural network
Unfortunately we can only provide so much help without a reproducible example.
Can you us
Unfortunately we can only provide so much help without a reproducible
example. Can you use a dataset that everyone would have access to to
reproduce the problem? Otherwise it is difficult for anyone to help you.
Regards,
Charles
On Tue, Mar 1, 2016 at 12:35 AM, jake88 wrote:
> I am new to R a
I am new to R and neural networks . So I trained and predicted an elman
network like so :
require ( RSNNS )
mydata = read.csv("mydata.csv",header = TRUE)
mydata.train = mydata[1000:2000,]
mydata.test = mydata[800:999,]
fit <- elman ( mydata.train[,2:10],mydata.train[,1], size =100
lear
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