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#101
04-13-2019, 07:23 PM
 NchooseK Member SOA Non-Actuary Join Date: Nov 2012 Location: Philly area College: Swarthmore College (BA Mathematics), Villanova University (MS Applied Stat) Posts: 353

Quote:
 Originally Posted by TranceBrah there is no analog. we would only use confusion matrixes for classifaction problems. the accuracy assessment would be the same as a linear model - simplest is MSE what are some things you feel are inadequate? It seems to answer everything fine to me?
If this is an offer to answer some of my questions, consider me quite appreciative.

1) We first fit the most complex regression tree (within constraints such as max depth, etc) by specifying CP=0. rpart uses x-validation to determine the prediction error for each level of the complexity parameter investigated.

2) Prune the tree by capturing the CP that minimizes the cross-validation error, xerror. (Is this cost complexity pruning??). The following output shoudl do this:
Code:
`pdt2 <- prune(dt2, cp = dt2\$cptable[which.min(dt2\$cptable[, "xerror"]), "CP"])`
Summarize and plot?
MSE values emerge in the output? Do anything with these yet?
Pruned tree plot shown and summarized with summary().
Estimates given for each split.

Next chunk uses 6-fold cross-validation folds and expands the grid to search for cp from 0, 0.05, 0.005.

3) The final model is fitted:
Code:
```caret1 <-train(dt2.f,
data = AutoClaim.training,
method = "rpart",
trControl = fitControl,
metric="RMSE",
tuneGrid = Grid,
na.action = na.pass)```
NO USE OR MENTION OF TEST/VALIDATION DATA SETS :/

Appropriate--I believe-- the *full* model runs the entire data set. Final model tree shown, along with CP vs RMSE (CV) plot.
I wish the validation/testing set(s) we not ignored in the only regression tree example.

I also didn't see any predict() functions; how do we determine the RMSE that "we report."

THANK YOU
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#102
04-13-2019, 08:25 PM
 TranceBrah Member SOA Join Date: Mar 2014 Location: Best Coast Posts: 255

Quote:
 Originally Posted by NchooseK I wish the validation/testing set(s) we not ignored in the only regression tree example. I also didn't see any predict() functions; how do we determine the RMSE that "we report."
Are you referring to the sample Student project or a module? They didn't use regression trees for that since it was a classification problem (pass or fail).

You can calculate ur own RMSE using ur predictions.
Get ur predictions from pred <- predict(tree.model, newdata = "testdata")
rmse <- sqrt(sum((pred - testdata\$target)^2)/length(testdata\$target))
#103
04-13-2019, 10:02 PM
 NchooseK Member SOA Non-Actuary Join Date: Nov 2012 Location: Philly area College: Swarthmore College (BA Mathematics), Villanova University (MS Applied Stat) Posts: 353

Quote:
 Originally Posted by TranceBrah Are you referring to the sample Student project or a module? They didn't use regression trees for that since it was a classification problem (pass or fail). You can calculate ur own RMSE using ur predictions. Get ur predictions from pred <- predict(tree.model, newdata = "testdata") rmse <- sqrt(sum((pred - testdata\$target)^2)/length(testdata\$target))
What you are written is helpful--so thank you.

FWIW, I am referring to ASA 7.2, which devotes as much time to the regression as secondary schools do to important black history figures not named MLK, Parks or Tubman.
__________________
Exams: P | FM | C | MFE | LTAM | SRM Credit | PA

VEE: Statistics | Finance | Economics

FAP: 1 | 2 | 3 | 4 | IA | 6 | 7 | FA

Conferences: APC
#104
04-14-2019, 08:19 PM
 Alec R - Davos Analytics Non-Actuary Join Date: Mar 2019 Posts: 7

Quote:
 Originally Posted by gaudettj I'm debating doing this in June. I studied GLMs at University, did pretty well on top of finding it interesting, so I'm not overly concerned about the technical side of it. Anybody think this is too short of a time frame to get through the modules and absorb the material?
We think it's doable. When making our study manual we spoke with multiple students who were successful in the first sitting and only started studying for it after writing LTAM.
#105
04-15-2019, 01:11 PM
 ActuariallyDecentAtBest Member SOA Join Date: Dec 2016 Posts: 409

Quote:
 Originally Posted by ShannonB1 You can register now. https://www.soa.org/Education/Exam-R...analytics.aspx
Thanks!
#106
04-16-2019, 07:23 AM
 RiskyBusiness7 Member SOA Join Date: Apr 2018 Posts: 56

anyone know where 1.12% is coming from on slide 75 of mod 6?
#107
04-16-2019, 11:46 AM
 DukeSilver Member SOA Join Date: Dec 2018 Location: Boise, ID Favorite beer: Black Butte Porter Posts: 112

Thank you NchooseK and avocado for the response, I appreciate it. Talked with my manager and am going to start studying after writing LTAM in 2 weeks! Oh boy.
#108
04-16-2019, 01:13 PM
 KarimZ Member SOA Join Date: May 2015 Location: Pakistan College: Graduate, Bsc Accounting and Finance Posts: 210

Anyone came across some video tutorials for R that are free and helpful?

Using the book R for Everyone and progressing very slowly. Still on Module 1 and Chapter 7 of the book, dont think Ill make it in time for the exam in June.
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#109
04-16-2019, 01:22 PM
 ActuariallyDecentAtBest Member SOA Join Date: Dec 2016 Posts: 409

Quote:
 Originally Posted by KarimZ Anyone came across some video tutorials for R that are free and helpful? Using the book R for Everyone and progressing very slowly. Still on Module 1 and Chapter 7 of the book, dont think Ill make it in time for the exam in June.
Seems pretty doable.
#110
04-16-2019, 08:05 PM
 Mancusian23 SOA Join Date: Oct 2017 Studying for PA College: Drake Posts: 5
Section 8.2

In section 8.2, the module keeps referring to the "elbow" in the attached graph and it goes on to say "they form three easily identified groups." Can someone help me find the elbow in the graph and how they got to the "easily identified" groups and the value conditions? I appreciate the help!
Attached Images

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