Use Bigglm in a sentence

1. Bigglm creates a generalized linear model object that uses only p^2 memory for p variables.

Bigglm

2. The Bigglm.data.frame method gives an example of how such a function might be written, another is in the Examples below

Bigglm, Be, Below

3. It returns an object of class "Bigglm" that inherits from class "glmnet"

Bigglm

4. Description Bigglm creates a generalized linear model object that uses only p^2 memory for p variables.

Bigglm

5. ## ## Make a linear model using biglm ## require(biglm) mymodel - Bigglm(payment ~ sex + age + place.served, data = x) summary(mymodel) # This will overflow your RAM as it will get your data from ff into RAM #summary(glm(payment ~ sex + age + place.served, data = x[,c("payment","sex","age","place.served")]))

Biglm, Bigglm

6. Bigglm.ffdf(formula, data, family = gaussian(),, where formula is something like Y~X, assuming Y and X correspond to the colnames of ffdf object called data

Bigglm

7. Bigglm on your big data set in open source R, it just works - similar as in SAS In a recent post by Revolution Analytics (link & link) in which Revolution was benchmarking their closed source generalized linear model approach with SAS, Hadoop and open source R, they seemed to be pointing out that there is no 'easy' R open source solution which exists for building a poisson regression model on

Bigglm, Big, By, Benchmarking, Be, Building

8. And Bigglm.big.matrix() functions;“biglm”stands for“bounded memory linear regression.” In this example, the movie release year is used (as a factor) to try to predict customer ratings: > lm.0 = biglm.big.matrix(rating ~ year, data = x, fc = "year")

Bigglm, Big, Biglm, Bounded

9. Bigglm does not provide a mechanism for setting factor levels on the fly

Bigglm

10. Model selection of biglm::Bigglm models is not so straightforward

Biglm, Bigglm

11. Description Bigglm.ffdf creates a generalized linear model object that uses only p^2 memory for p variables

Bigglm

12. System.time(Bigglm(DepDelay~DayOfWeek+DepTime+CRSDepTime+ArrTime+CRSArrTime+UniqueCarrier, data=x)) # user system elapsed # 70.087 15.587 103.662 Now wasn’t that a lot better

Bigglm, Better

13. Using the Bigglm() function we got results about 23 times faster.

Bigglm

14. A biglm object created by a call to biglm::biglm() or biglm::Bigglm()

Biglm, By, Bigglm

15. I am simulating data and comparing glm.fit , Bigglm, speedglm, glmnet, LiblineaR for binary logit model

Bigglm, Binary

16. 0.9 fix ODBC and DBI interfaces for Bigglm to not use LIMIT, and just not allow variables to be floating free in the workspace (which really couldn't work anyway) fix arguably-false-positive from Fortran bounds checking, by incorporating the fix in the published AS274 0.8 allow offsets in model formulas for both biglm and Bigglm.

Bigglm, Be, Bounds, By, Both, Biglm

17. Biglm and Bigglm (chunked fitting with package biglm) Bootstrapping (chunked and parallelized random access) Bagged predictive modelling (chunked and parallelized random access) Bagged clustering (chunked and parallelized random access with truecluster) Likelihood maximization (chunked and parallelized sequential access)

Biglm, Bigglm, Bootstrapping, Bagged

18. Bigglm creates a generalized linear model object that uses only p^2 memory for p variables.: 2

Bigglm

19. Bigglm 7 Bigglm fit a glm with all the options in glmnet Description Fit a generalized linear model as in glmnet but unpenalized

Bigglm, But

20. Usage Bigglm(x, , path = FALSE) Arguments x input matrix Most other arguments to glmnet that make sense

Bigglm

21. According to the documentation trail, Bigglm () is based on Alan Miller’s 1991 refinement (algorithm AS 274 implemented in Fortran 77) to W

Bigglm, Based

22. Library (ffbase) library (biglm) library (ff) data (trees) x <- as.ffdf (trees) a <- Bigglm.ffdf (log (Volume)~log (Girth)+log (Height), data=x, chunksize=10, sandwich=TRUE)

Biglm, Bigglm

23. Bigglm does not provide a mechanism for setting factor levels on the fly

Bigglm

24. A biglm object created by a call to biglm::biglm() or biglm::Bigglm()

Biglm, By, Bigglm

25. Bigglm() fit a glm with all the options in glmnet

Bigglm

26. \ code {\ link [biglm: Bigglm]{biglm:: Bigglm()}}.} \ item {}{Additional arguments

Biglm, Bigglm

27. > lmRDemo <-Bigglm(Id~x1+x2,data=airpoll) >summary(lmRDemo) Large data regression model: Bigglm(Id ~ x1 + x2, data = airpoll) Sample size = 1e+06 Coef (95% CI) SE p (Intercept) 499583.8466 498055.6924 501112.0007 764.0771 0.0000 x1 -603.1151 -2602.7075 1396.4774 999.7962 0.5464

Bigglm

28. The Bigglm function came later and the models other than Gaussian require multiple passes through the data so instead of the update mechanism that biglm uses, Bigglm requires the data argument to be a function that returns the next chunk of data and can restart to the beginning of the dataset.

Bigglm, Biglm, Be, Beginning

29. Faster than Bigglm or other big data functions in R

Bigglm, Big

30. System.time(Bigglm(DepDelay~DayOfWeek+DepTime+CRSDepTime+ArrTime+CRSArrTime+UniqueCarrier, data=x)) # user system elapsed # 70.087 15.587 103.662 Now wasn’t that a lot better

Bigglm, Better

31. Using the Bigglm() function we got results about 23 times faster.

Bigglm

32.

Up to$5cash back

Back, Bigglm

33. To do this, you would open a database connection using RODBC or RSQLite and then call Bigglm with the data argument specifying the database connection and tablename specifying the …

Bigglm

34. Bigglm.big.matrix, bigkmeans, binit, and applyfor big.matrixobjects

Bigglm, Big, Bigkmeans, Binit

35. Bigglm() , from the package biglm by Thomas Lumley

Bigglm, Biglm, By

36. The Bigglm function in the biglm package does the iteration using bounded memory, by reading in the data in chunks, and starting again at the beginning for each iteration

Bigglm, Biglm, Bounded, By, Beginning

37. Bigglm iterations If p is not too large and the data are reasonably well-behaved so that the loglikelihood is well-approximated by a quadratic, three iterations should be sufficient and good starting values will cut this to two iterations or even to one

Bigglm, Behaved, By, Be

38. Value It returns an object of class "Bigglm" that inherits from class "glmnet"

Bigglm

39. 내가 데이터를 시뮬레이션 이진 로짓 모델 glm.fit, Bigglm, speedglm, glmnet, LiblineaR을 비교하고를 사용하여 로지스틱 회귀 분석을 벤치마킹.

Bigglm