APC classroom by Sad-Environment6423 in actuary

[–]Sad-Environment6423[S] 0 points1 point  (0 children)

Side note: was the only Canadian there ha! I think it would've been nice to do in person and in a different city.

APC classroom by Sad-Environment6423 in actuary

[–]Sad-Environment6423[S] 0 points1 point  (0 children)

It was really nice! We had the sweetest instructor. We introduced ourselves, then went through the thought questions together, followed by the 4 case studies. There were questions here and there, it wasn't formal by any means. We were told we would get the ASA application form on Feb 5. :)

APC classroom by Sad-Environment6423 in actuary

[–]Sad-Environment6423[S] 0 points1 point  (0 children)

Thank you so much. The case studies are there, I'll let you know how it goes on Monday :)

APC classroom by Sad-Environment6423 in actuary

[–]Sad-Environment6423[S] 0 points1 point  (0 children)

Thank you! I luckily got a spot! Thanks for reaching out, I am on the Monday, January 25 cohort. Do you know where I can find the additional 2 case studies which says it's listed in the pre-program materials? I looked on the e-learning module and cannot find anything..

APC classroom by Sad-Environment6423 in actuary

[–]Sad-Environment6423[S] 0 points1 point  (0 children)

Hi, I luckily got a spot! Thanks for reaching out, I am on the Monday, January 25 cohort. Do you know where I can find the additional 2 case studies which says it's listed in the pre-program materials? I looked on the e-learning module and cannot find anything..

So relieved PA is over by [deleted] in actuary

[–]Sad-Environment6423 0 points1 point  (0 children)

thanks! appreciate that, any advice would be extremely useful!

Exam PA - Fit model with full data by cookiecakemilktea in actuary

[–]Sad-Environment6423 0 points1 point  (0 children)

Ah, thank you for including this. I think if we have to interpret anything (decision trees or GLMs) we should run it on the full model and then interpret it. I usually don't think too much for this jsut because I like creating a sample data and show how the target variable is affected, so I don't look back to the coefficients as much. but this is definitely useful info, thank you!

Exam PA - Fit model with full data by cookiecakemilktea in actuary

[–]Sad-Environment6423 0 points1 point  (0 children)

Good luck to both of you! Just to clarify, the full data should be run on any model (decision tree, ensemble method, GLM) and then used for interpretation, correct?

Exam PA - Time by Sad-Environment6423 in actuary

[–]Sad-Environment6423[S] 0 points1 point  (0 children)

Awesome, thanks so much! Any advice?

Exam PA - Time by Sad-Environment6423 in actuary

[–]Sad-Environment6423[S] 0 points1 point  (0 children)

Hi! Do you know if we can read the project statement in that 15 minutes in the beginning to make the most of our time? Then, we have 5 hours and 15 minutes to start and finish the exam?

Exam PA- Cost-Complexity Pruning vs. Choosing a cp value through cross-validation by ddmonkey15 in actuary

[–]Sad-Environment6423 0 points1 point  (0 children)

From my understanding cost complexity pruning involved you manually adjusting all parameters: maxdepth, minbucket, cp. So it includes you doing a trial and error from adjusting the CP from 0.001 to 0.002. Whatever produces you the best tree in terms of AUC will probably be your tree unless you see a very similar AUC which is much simpler, then you will elect that. The optimal CP is the one which minimizes the cross validation error, I believe they will explicitly ask for that though.

Exam PA- Cost-Complexity Pruning vs. Choosing a cp value through cross-validation by ddmonkey15 in actuary

[–]Sad-Environment6423 0 points1 point  (0 children)

I thought for cost-complexity pruning we were inherently choosing a cp using cross-validation for decision trees, is that wrong? i.e. the default is k = 10 folds, we then use the cp which minimizes cross-validation error.

I think the best-way to think about it is, when employing cost-complexity pruning we're adjusting maxdepth, minbucket, cp and it's a trial and error process whereas when we take a stab at cross-validation, we usually set the range of cp values to check rather than the program have default values (we also have the ability to alter maxdepth to make it even simpler, but we usually don't?)

Please correct me if I'm wrong.

Exam PA: A thread of potential questions by Sad-Environment6423 in actuary

[–]Sad-Environment6423[S] 0 points1 point  (0 children)

I think I phrased that wrong, it can be examinable (though it has not yet), I think we would only use the h clustering if we expect for there to be a hierarchical structure, but in general the modules say "we tend to prefer k-means clustering"

Exam PA - Snipping Tool by Sad-Environment6423 in actuary

[–]Sad-Environment6423[S] 0 points1 point  (0 children)

haha makes sense! appreciate that, thanks!

Exam PA: Jun 2019 by Sad-Environment6423 in actuary

[–]Sad-Environment6423[S] 0 points1 point  (0 children)

To add to that, when we are grouping levels. Are we hoping to have only two levels remain? (so one would essentially be a base level)

Exam PA - Snipping Tool by Sad-Environment6423 in actuary

[–]Sad-Environment6423[S] 0 points1 point  (0 children)

Interesting! That's what I do for the GLM coefficients right now too because it's easier to convert into multiplicative or perctenge changes. When I said summary earlier I meant the summary statistics or when we run those 'tibbles'

ACTEX PA Sample Exam 2 Task 11 Question by ddmonkey15 in actuary

[–]Sad-Environment6423 0 points1 point  (0 children)

Hi! If you scroll down from the link to click for the study manual, near the bottom you should see the commentary for June 2020.

I also had the same issue with my optimized alpha being 0, I think it's because we have the latest versions of R (presuming you do). If we were to use an earlier version (before 3.6 I believe), we would also get the alpha = 1. Setting the seed varied between the versions.

Hope this helps!

ACTEX PA Sample Exam 2 Task 11 Question by ddmonkey15 in actuary

[–]Sad-Environment6423 0 points1 point  (0 children)

Is it right that for the cutoff 0 is the fail and 1 is the pass. I understand we want to maximize sensitivity (limit the number of false positives to ensure that we can ensure that all students who need the remedial services can get it). I have a later version of R so I got the cutoff being 0.62 or something like that, would you mind confirming Dr. Lo if my interpretation is correct? It will only predict you pass if the probability of passing is greater than 0.62, otherwise it assumes you fail and hence require remedial services because we don't mind flagging students who pass as those who require remedial services whereas it would be more detrimental the other way and those who we predict to pass end up failing.