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Accuracy problems in estimating pi using Machin's method


Accuracy problems in estimating pi using Machin's method

By : Yerlan
Date : October 17 2020, 06:10 PM
Does that help Okay I have figured this problem out. I don't know why this happens in python but calling the function I wrote like this machinpi(Decimal(1/5), Decimal(1/239), terms) is not equal to this which has the accuracy that I expect machinpi(Decimal(1)/Decimal(5), Decimal(1)/Decimal(239), terms)
code :


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Syncing programs across different machins

Syncing programs across different machins


By : AchillesLy
Date : March 29 2020, 07:55 AM
hope this fix your issue I actually found out that rsync does the job perfectly. I just needed -c option. The option asks rsync to just copy the changed files over. I works fine yet there are some minor issues with the make due to the timing difference between the two machines.
How does Keras compute validation accuracy and training accuracy for multi-class classification problems?

How does Keras compute validation accuracy and training accuracy for multi-class classification problems?


By : Daniel Giannopolo
Date : March 29 2020, 07:55 AM
This might help you You can find the metrics file and their implementation in the Keras github repo. In this case following metric applies:
code :
def categorical_accuracy(y_true, y_pred):
    return K.cast(K.equal(K.argmax(y_true, axis=-1),
                          K.argmax(y_pred, axis=-1)),
                          K.floatx()) 
(amount of correct guesses)/(total amount of guesses) 
Estimating difficulty of instances of NP problems

Estimating difficulty of instances of NP problems


By : quid pro quo
Date : March 29 2020, 07:55 AM
hop of those help? This is the same problem faced by researchers trying to create public-key encryption algorithms based on np-completeness. As far as I know, there are some stabs at it, but it's still an open problem. See the discussion here: Are there public key cryptography algorithms that are provably NP-hard to defeat?
I know I've seen more recent work, but can't find it offhand. I recall a book composed of articles about alternative cryptosystems should factorization suddenly become cheap, and I'll try to dig up the link.
Estimating prediction accuracy of a Cox survival model using sbrier (R)

Estimating prediction accuracy of a Cox survival model using sbrier (R)


By : Dinh Do
Date : March 29 2020, 07:55 AM
hope this fix your issue The integrated Brier score (IBS) has been suggested in a paper by Graf et al (1999) as a good measure for prediction accuracy in survival models (see e.g. overview paper by Wiering et al., page 23). , You can use the pec package, instead.
Example:
Estimating accuracy with (x == y).mean() - How does it work?

Estimating accuracy with (x == y).mean() - How does it work?


By : Junsu Jo
Date : March 29 2020, 07:55 AM
should help you out truth is an array of labels. pred is an array of predictions by the model. In an ideal situation, truth must equal pred. However, practically, there will be errors in the model's prediction. Thus, the concept of accuracy which measures how many data points the model predicted correctly.
Assuming these are numpy arrays,
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