Last updated: 2018-03-06

Code version: e16e34a

R.matlab v3.6.1 (2016-10-19) successfully loaded. See ?R.matlab for help.

Attaching package: 'R.matlab'
The following objects are masked from 'package:base':

    getOption, isOpen

MovieLens 100K data:

The data contains about 100K user-movie ratings (integers from 1 to 5) from approximately 1000 users across a total of 1700 movies. Most users do not rate most movies, so the matrix is sparsely observed (94% missing). We centered and scaled the ratings for each user before applying methods to these data.

ml100K_data = readRDS("../data/scale_data.rds")
MLMatrix <- sparseMatrix(i = ml100K_data[,1],
                         j = ml100K_data[,2],
                         x = ml100K_data[,3],dims = c(943,1682))
# turn this sparse matrix into matrix in r
Y = as.matrix(MLMatrix)
Y[which(Y == 0)] = NA

Flash:

flash_data = flash_set_data(Y)
fmodel = flash(flash_data, greedy = TRUE, backfit = TRUE)

saveRDS(fmodel, '../output/MovieLensVarCol.rds')

Flash again on the loading matrix

flash_loading = flash_set_data(fmodel$EL[,1:5])
flmodel = flash(flash_loading, ebnm_fn = ebnm_ash, backfit = TRUE, greedy = TRUE)

The flash prefers the rank 0 model. There is no hidden structure in the loading matrix.

Session information

sessionInfo()
R version 3.4.3 (2017-11-30)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS High Sierra 10.13.3

Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] Matrix_1.2-12  R.matlab_3.6.1 flashr_0.5-6  

loaded via a namespace (and not attached):
 [1] Rcpp_0.12.15      compiler_3.4.3    git2r_0.20.0     
 [4] plyr_1.8.4        R.utils_2.6.0     R.methodsS3_1.7.1
 [7] iterators_1.0.9   tools_3.4.3       digest_0.6.13    
[10] evaluate_0.10.1   tibble_1.3.4      gtable_0.2.0     
[13] lattice_0.20-35   rlang_0.1.6       foreach_1.4.4    
[16] yaml_2.1.17       parallel_3.4.3    ebnm_0.1-10      
[19] stringr_1.3.0     knitr_1.20        rprojroot_1.2    
[22] grid_3.4.3        rmarkdown_1.8     ggplot2_2.2.1    
[25] ashr_2.2-7        magrittr_1.5      backports_1.1.2  
[28] scales_0.5.0      codetools_0.2-15  htmltools_0.3.6  
[31] MASS_7.3-47       assertthat_0.2.0  softImpute_1.4   
[34] colorspace_1.3-2  stringi_1.1.6     lazyeval_0.2.1   
[37] pscl_1.5.2        doParallel_1.0.11 munsell_0.4.3    
[40] truncnorm_1.0-8   SQUAREM_2017.10-1 R.oo_1.21.0

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