Hello, this is not the right forum, but I appeal to the community:
I made a process using R, changing only inputs and outputs to generate a
supervised classification and gives me the following data at the end:
Calculating random forest object
Starting predictions
#################################################################################
*OOB error rate estimate*
*0.007407407%*
Confusion matrix
1 2 3 4 class.error
1 101 0 0 0 0.000000000
2 0 101 0 0 0.000000000
3 0 0 101 1 0.009803922
4 0 1 1 99 0.019801980
Hello, this is not the right forum, but I appeal to the community:
I made a process using R, changing only inputs and outputs to generate a
supervised classification and gives me the following data at the end:
So: 1. What does OOB mean in itself? 2. In what range or interval should
the OOB value be so that the prediction is better?
Thank you
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