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RNN trainr issue #32
Description
Hello, I am getting an error running the trainr command in the package. Here it is:
Error in if (dim(X)[2] != dim(Y)[2] && !seq_to_seq_unsync) { :
missing value where TRUE/FALSE needed
Even though X and Y are the same length. I have copied the R file with my code:
library(rnn)
library(corrplot)
prices <- read.csv('A:\Vasu\Big Data Masters\MRP\Clean Input.csv')
prices$Date <- NULL
prices$Gold.Price <- as.numeric(gsub(",","", as.character(just_prices$Gold.Price), fixed = TRUE))
prices$DJIA <- as.numeric(gsub(",","", as.character(just_prices$DJIA), fixed = TRUE))
matrix <- cor(prices)
corrplot(matrix, method = "circle")
model <- trainr(Y = array(prices$Gold.Price), X = array(prices$US.Dollar.Index) , learningrate = 0.1,
sigmoid = 'logistic', use_bias = T)
Activity
bquast commentedon Jun 21, 2018
@DimitriF any thoughts?
DimitriF commentedon Jun 21, 2018
I think
arraywithout thedimargument will return a array with one dimension, it seems you have only one sample, this should work better:vasgupta commentedon Jun 21, 2018
Thanks @DimitriF it worked!
vasgupta commentedon Jun 21, 2018
But just one more question, what if I wanted to input 3 variables, instead of one?
I tried this, but its not working.
model <- trainr(Y = array(prices$Gold.Price,dim=c(1,nrow(prices))),
X = array(c(prices$US.Dollar.Index, prices$CBOE.Volatility, prices$Silver.Price),
dim=c(3,nrow(prices))) , learningrate = 0.1,
sigmoid = 'logistic', use_bias = T)
DimitriF commentedon Jun 21, 2018
the first dimension is for the number of samples, the second for the number of elements in the sequence and the optional third dimension for the number of variables (if only 2 dimensions, yu have only one variable), so it should look like this:
But I am not sure how
arrayfill itself so you may have to useapermto checkvasgupta commentedon Jun 29, 2018
Hey, just wanted to clarify an issue I was getting.
I'm running the RNN with just one variable and I convert all my inputs to binary before training on the RNN. However, in the output I was expecting a binary output, but it gave me a decimal answer. How can I fix this?
Here's my code:
prices <- read.csv('A:\Vasu\Big Data Masters\MRP\Clean Input.csv')
prices$Date <- NULL
prices$Gold.Price <- as.numeric(gsub(",","", as.character(just_prices$Gold.Price), fixed = TRUE))
prices$DJIA <- as.numeric(gsub(",","", as.character(just_prices$DJIA), fixed = TRUE))
matrix <- cor(prices)
corrplot(matrix, method = "circle")
convert integer prices to binary
Y <- int2bin(prices$Gold.Price)
X <- int2bin(prices$US.Dollar.Index)
test <- int2bin(Test_prices$US.Dollar.Index)
model <- trainr(Y = Y,
X = X , learningrate = 0.1,
sigmoid = 'logistic', use_bias = T)
result <- predictr(model, test)
DimitriF commentedon Jun 30, 2018
round(result)?vasgupta commentedon Jun 30, 2018
My results look like this:
bquast commentedon Jun 30, 2018
All below 0.5? There must be another problem then
vasgupta commentedon Jun 30, 2018
Does the input have to be in binary?
vasgupta commentedon Jun 30, 2018
As well the int2bin function doesn't properly convert the integer to binary, it gives a wrong number.
bquast commentedon Jul 2, 2018
Not the input, nor the output has to be binary, the binary stuff is simply an example.