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I tried to model few linear mixed models... #9

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englianhu opened this issue Oct 30, 2020 · 3 comments
Open

I tried to model few linear mixed models... #9

englianhu opened this issue Oct 30, 2020 · 3 comments
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@englianhu
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englianhu commented Oct 30, 2020

Video from awesomescreenshot.com

Click the link below to watch the video:
https://www.awesomescreenshot.com/video/1547059?key=7be26eec34173b989d245d0d8b3f32ed

Running 3 days for above 3 models, existing hp PC (bought in 2015) unable support desktop visualization and running programming... need to buy a new PC when affort

@englianhu englianhu added the help wanted Extra attention is needed label Oct 30, 2020
@englianhu englianhu changed the title no issue I tried to model few linear mixed models... Oct 30, 2020
@englianhu
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Screenshot_1


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@englianhu
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englianhu commented Nov 6, 2020

englianhu/binary.com-interview-question#1
use sparklyr but believe dataset not high-volume, will apply to HFT in https://github.com/englianhu/binary.com-interview-question

> microbenchmark(
+     spark = 
+         smp2_sc %>% 
+             ml_linear_regression(Profit ~ .), 
+     normal = lm(Profit ~., smp2))
Unit: milliseconds
   expr       min         lq       mean    median        uq       max neval
  spark 3213.3874 3416.97000 3620.63197 3558.2209 3774.3810 5413.4950   100
 normal   24.5953   27.57015   29.66484   28.7103   30.0822   87.2707   100
> microbenchmark(
+     spark = 
+         smp2_sc %>% 
+             ml_linear_regression(Profit ~ .), 
+     normal = lm(Profit ~., smp2))
Unit: milliseconds
   expr       min         lq       mean     median         uq       max neval
  spark 3223.9533 3372.34675 3512.10774 3491.44990 3589.48430 4277.6933   100
 normal   25.6651   27.14775   28.81245   28.06895   29.51575   49.0671   100

here's reference to speed up lm:

@englianhu
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englianhu commented Nov 8, 2020

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