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I realize that this question is answered at the following thread I have created a batch file to check if scheduled task exists and if they don't create them, however, my if exist rule seem to always hit true even though the jobs are not there Specifying the running directory for scheduled tasks using schtasks.exe however, i'm still having trouble understanding the answ.
I am using sklearn.metrics.confusion_matrix(y_actual, y_predict) to extract tn, fp, fn, tp and most of the time it works perfectly Generally for equations like t(n) = 2t(n/2) + c (gi. Tn.write('exit\n') btw, telnetnetlib can be tricky and things varies depending on your ftp server and environment setup
You might be better off looking into something like pexpect to automate login and user interaction over telnet.
Thanks walter for your comments Weka gives me tp rate for each of the class so is that the same value which comes from confusion matrix That's what i want to know Second is i want to calculate those values by hand (if weka give those values i don't mind)
I am using weka gui for the same. I'm using python's telnetlib to telnet to some machine and executing few commands and i want to get the output of these commands A true negative (tn) is, by definition, everything that is not birth year recognized as not birth year In the context, every token/word different from 2000 identified as not birth year is a tn
If you want more example, you can find them in the supplementary information of this paper i wrote at section fine tuning and evaluation metrics
Tp+fp+tn+fn = 94135.1205 the total sum is now reduced further by 45574 Same is true for epochs lower down the order Shouldn't the total sum be the same If not then why does it keep on decreasing
Part 3 why are the values for tp, fp, fn, tn in both training and validation floating numbers As per my understanding these should always be integer. In cormen's introduction to algorithm's book, i'm attempting to work the following problem I want to understand how to arrive at the complexity of the below recurrence relation
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