On Mon, Jul 18, 2011 at 06:36:13AM -0400, Sarah Goslee wrote:
> Your data1 and your data1_class file differ in the first three
> columns. Assuming that's an error, here's one way to do it:
>
> > data1 <- data.frame(layer1=c(.2, .5, .2, .8, .2, .5, .5, .8, .2,
> > .8),layer2=c(2,3,2,2,1,2,3,2,2,2)
Also read FAQ 7.31 before using 'numerics' as grouping factors.
On Mon, Jul 18, 2011 at 6:36 AM, Sarah Goslee wrote:
> Your data1 and your data1_class file differ in the first three
> columns. Assuming that's an error, here's one way to do it:
>
>> data1 <- data.frame(layer1=c(.2, .5, .2, .8, .2,
Your data1 and your data1_class file differ in the first three
columns. Assuming that's an error, here's one way to do it:
> data1 <- data.frame(layer1=c(.2, .5, .2, .8, .2, .5, .5, .8, .2,
> .8),layer2=c(2,3,2,2,1,2,3,2,2,2), layer3=c(1,1,1,1,1,1,1,1,1,4))
> data1 <- cbind(data1, class=as.numeri
Hi,
I need to make a cluster classification by the unique values of the data frame.
I explain the problem. I need to classify this table, and assign to
the same cluster each row that has the same combination of value:
> data1
layer_1 layer_2 layer_3
[1,] 0.246000 2
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