I am running H2O 3.10.5.3 (on hadoop cdh5.8) on a remote server, connected to my local machine using R (3.4.1) with 'h2o.init(startH2O=F, port=54321)'.
The code below works fine:
Train.hex <- as.h2o(iris)
h2o.gbm(x="Sepal.Length", y="Petal.Width", training_frame = Train.hex)
but xgboost does not work and generates the following error message:
h2o.xgboost(x="Sepal.Length", y="Petal.Width", training_frame = Train.hex)
ERROR: Unexpected HTTP Status code: 500 Server Error (url = http://localhost:54321/3/ModelBuilders/xgboost)
java.lang.ArrayIndexOutOfBoundsException
[1] "java.lang.ArrayIndexOutOfBoundsException: -1"
[2] " hex.ModelBuilder.make(ModelBuilder.java:117)"
[3] " water.api.ModelBuildersHandler.fetch(ModelBuildersHandler.java:35)"
[4] " sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)"
[5] " sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)"
[6] " sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)"
[7] " java.lang.reflect.Method.invoke(Method.java:498)"
[8] " water.api.Handler.handle(Handler.java:63)"
[9] " water.api.RequestServer.serve(RequestServer.java:448)"
[10] " water.api.RequestServer.doGeneric(RequestServer.java:297)"
[11] " water.api.RequestServer.doGet(RequestServer.java:221)"
[12] " javax.servlet.http.HttpServlet.service(HttpServlet.java:707)"
[13] " javax.servlet.http.HttpServlet.service(HttpServlet.java:820)"
[14] " org.eclipse.jetty.servlet.ServletHolder.handle(ServletHolder.java:684)"
[15] " org.eclipse.jetty.servlet.ServletHandler.doHandle(ServletHandler.java:503)"
[16] " org.eclipse.jetty.server.handler.ContextHandler.doHandle(ContextHandler.java:1086)"
[17] " org.eclipse.jetty.servlet.ServletHandler.doScope(ServletHandler.java:429)"
[18] " org.eclipse.jetty.server.handler.ContextHandler.doScope(ContextHandler.java:1020)"
[19] " org.eclipse.jetty.server.handler.ScopedHandler.handle(ScopedHandler.java:135)"
[20] " org.eclipse.jetty.server.handler.HandlerCollection.handle(HandlerCollection.java:154)"
[21] " org.eclipse.jetty.server.handler.HandlerWrapper.handle(HandlerWrapper.java:116)"
[22] " water.JettyHTTPD$LoginHandler.handle(JettyHTTPD.java:183)"
[23] " org.eclipse.jetty.server.handler.HandlerCollection.handle(HandlerCollection.java:154)"
[24] " org.eclipse.jetty.server.handler.HandlerWrapper.handle(HandlerWrapper.java:116)"
[25] " org.eclipse.jetty.server.Server.handle(Server.java:366)"
[26] " org.eclipse.jetty.server.AbstractHttpConnection.handleRequest(AbstractHttpConnection.java:494)"
[27] " org.eclipse.jetty.server.BlockingHttpConnection.handleRequest(BlockingHttpConnection.java:53)"
[28] " org.eclipse.jetty.server.AbstractHttpConnection.headerComplete(AbstractHttpConnection.java:971)"
[29] " org.eclipse.jetty.server.AbstractHttpConnection$RequestHandler.headerComplete(AbstractHttpConnection.java:1033)"
[30] " org.eclipse.jetty.http.HttpParser.parseNext(HttpParser.java:644)"
[31] " org.eclipse.jetty.http.HttpParser.parseAvailable(HttpParser.java:235)"
[32] " org.eclipse.jetty.server.BlockingHttpConnection.handle(BlockingHttpConnection.java:72)"
[33] " org.eclipse.jetty.server.bio.SocketConnector$ConnectorEndPoint.run(SocketConnector.java:264)"
[34] " org.eclipse.jetty.util.thread.QueuedThreadPool.runJob(QueuedThreadPool.java:608)"
[35] " org.eclipse.jetty.util.thread.QueuedThreadPool$3.run(QueuedThreadPool.java:543)"
[36] " java.lang.Thread.run(Thread.java:745)"
Error in .h2o.doSafeREST(h2oRestApiVersion = h2oRestApiVersion, urlSuffix = page, :
ERROR MESSAGE:
-1
Can anyone help me to understand what is going on?
Many thanks in advance,
Kere
Unfortunately, H2O Xgboost is not supported for the time being on Windows as also the official documentation of H2O states:
Limitations
This section provides a list of XGBoost limitations - some of which
will be addressed in a future release.
...
XGBoost is not supported on Windows.
...
XGBoost is not supported on Windows.
The list of limitations include:
XGBoost is not supported on Windows.
The list of supported platforms includes:Linux or OS X
When I met same issue I open my COLAB account and I try there. It did work for me.
Related
I am relatively new to Julia, which I started using for data science and machine learning. I have been working with DataFrames.jl and DataFramesMeta.jl which worked just fine until a few days ago.
I noticed that I kept getting the LoadError: UndefVarError: #rtransform not defined when using row-wise operations such as #rtransform and #rsubset, which did not happen previously. Furthermore, when I use the #byrow macro with #transform, I also get the error LoadError: ArgumentError: This path should not be reached.
For some reason, there is no stack trace for the UndefVarError.
The stack trace for the ArgumentError is as follows:
[1] fun_to_vec(ex::Expr; nolhs::Bool, gensym_names::Bool, wrap_byrow::Bool)
# DataFramesMeta ~/.julia/packages/DataFramesMeta/z0mc6/src/parsing.jl:302
[2] (::DataFramesMeta.var"#28#29"{Bool})(ex::Expr)
# DataFramesMeta ./none:0
[3] iterate(::Base.Generator{Vector{Any}, DataFramesMeta.var"#28#29"{Bool}})
# Base ./generator.jl:47
[4] transform!_helper(x::Symbol, args::Expr)
# DataFramesMeta ~/.julia/packages/DataFramesMeta/z0mc6/src/macros.jl:881
[5] var"#transform!"(__source__::LineNumberNode, __module__::Module, x::Any, args::Vararg{Any})
# DataFramesMeta ~/.julia/packages/DataFramesMeta/z0mc6/src/macros.jl:963
[6] eval
# ./boot.jl:373 [inlined]
[7] include_string(mapexpr::typeof(REPL.softscope), mod::Module, code::String, filename::String)
# Base ./loading.jl:1196
[8] invokelatest(::Any, ::Any, ::Vararg{Any}; kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
# Base ./essentials.jl:716
[9] invokelatest(::Any, ::Any, ::Vararg{Any})
# Base ./essentials.jl:714
[10] inlineeval(m::Module, code::String, code_line::Int64, code_column::Int64, file::String; softscope::Bool)
# VSCodeServer ~/.vscode/extensions/julialang.language-julia-1.6.28/scripts/packages/VSCodeServer/src/eval.jl:238
[11] (::VSCodeServer.var"#66#70"{Bool, Bool, Bool, Module, String, Int64, Int64, String, VSCodeServer.ReplRunCodeRequestParams})()
# VSCodeServer ~/.vscode/extensions/julialang.language-julia-1.6.28/scripts/packages/VSCodeServer/src/eval.jl:162
[12] withpath(f::VSCodeServer.var"#66#70"{Bool, Bool, Bool, Module, String, Int64, Int64, String, VSCodeServer.ReplRunCodeRequestParams}, path::String)
# VSCodeServer ~/.vscode/extensions/julialang.language-julia-1.6.28/scripts/packages/VSCodeServer/src/repl.jl:219
[13] (::VSCodeServer.var"#65#69"{Bool, Bool, Bool, Module, String, Int64, Int64, String, VSCodeServer.ReplRunCodeRequestParams})()
# VSCodeServer ~/.vscode/extensions/julialang.language-julia-1.6.28/scripts/packages/VSCodeServer/src/eval.jl:160
[14] hideprompt(f::VSCodeServer.var"#65#69"{Bool, Bool, Bool, Module, String, Int64, Int64, String, VSCodeServer.ReplRunCodeRequestParams})
# VSCodeServer ~/.vscode/extensions/julialang.language-julia-1.6.28/scripts/packages/VSCodeServer/src/repl.jl:38
[15] (::VSCodeServer.var"#64#68"{Bool, Bool, Bool, Module, String, Int64, Int64, String, VSCodeServer.ReplRunCodeRequestParams})()
# VSCodeServer ~/.vscode/extensions/julialang.language-julia-1.6.28/scripts/packages/VSCodeServer/src/eval.jl:126
[16] with_logstate(f::Function, logstate::Any)
# Base.CoreLogging ./logging.jl:511
[17] with_logger
# ./logging.jl:623 [inlined]
[18] (::VSCodeServer.var"#63#67"{VSCodeServer.ReplRunCodeRequestParams})()
# VSCodeServer ~/.vscode/extensions/julialang.language-julia-1.6.28/scripts/packages/VSCodeServer/src/eval.jl:230
[19] #invokelatest#2
# ./essentials.jl:716 [inlined]
[20] invokelatest(::Any)
# Base ./essentials.jl:714
[21] macro expansion
# ~/.vscode/extensions/julialang.language-julia-1.6.28/scripts/packages/VSCodeServer/src/eval.jl:34 [inlined]
[22] (::VSCodeServer.var"#61#62")()
# VSCodeServer ./task.jl:429
I am using the lines using DataFrames and using DataFramesMeta, so I do not have an idea as to why I am running into this error.
Any help is appreciated!
I tried to use ggplot2 in julia by RCall, like example below
using DataFrames
using RCall
df = DataFrame(randn(10,2),:auto)
#rlibrary ggplot2
#rlibrary ggsci
ggplot(df, aes(x=:x1, y=:x2))+geom_point()
It works well in the REPL, but in jupyter notebook something goes wrong, as the debug info below
REvalError: Warning in (function (filename = "Rplot%03d.png", width = 480, height = 480, :
locale not supported by Xlib: some X ops will operate in C locale
Warning in (function (filename = "Rplot%03d.png", width = 480, height = 480, :
X cannot set locale modifiers
Error in grid.Call(C_stringMetric, as.graphicsAnnot(x$label)) :
X11 font -adobe-helvetica-%s-%s-*-*-%d-*-*-*-*-*-*-*, face 1 at size 9 could not be loaded
Calls: <Anonymous> ... grid.Call -> <Anonymous> -> descentDetails.text -> grid.Call
Stacktrace:
[1] handle_eval_stderr(; as_warning::Bool)
# RCall ~/.julia/packages/RCall/iMDW2/src/io.jl:162
[2] rprint(io::IOContext{IOBuffer}, s::Ptr{VecSxp})
# RCall ~/.julia/packages/RCall/iMDW2/src/io.jl:36
[3] rprint
# ~/.julia/packages/RCall/iMDW2/src/io.jl:46 [inlined]
[4] show
# ~/.julia/packages/RCall/iMDW2/src/io.jl:52 [inlined]
[5] show
# ./multimedia.jl:47 [inlined]
[6] limitstringmime(mime::MIME{Symbol("text/plain")}, x::RObject{VecSxp})
# IJulia ~/.julia/packages/IJulia/e8kqU/src/inline.jl:43
[7] display_mimestring
# ~/.julia/packages/IJulia/e8kqU/src/display.jl:71 [inlined]
[8] display_dict(x::RObject{VecSxp})
# IJulia ~/.julia/packages/IJulia/e8kqU/src/display.jl:102
[9] #invokelatest#2
# ./essentials.jl:708 [inlined]
[10] invokelatest
# ./essentials.jl:706 [inlined]
[11] execute_request(socket::ZMQ.Socket, msg::IJulia.Msg)
# IJulia ~/.julia/packages/IJulia/e8kqU/src/execute_request.jl:112
[12] #invokelatest#2
# ./essentials.jl:708 [inlined]
[13] invokelatest
# ./essentials.jl:706 [inlined]
[14] eventloop(socket::ZMQ.Socket)
# IJulia ~/.julia/packages/IJulia/e8kqU/src/eventloop.jl:8
[15] (::IJulia.var"#15#18")()
# IJulia ./task.jl:411
I tried to save the picture in pdf, png or svg format, and only pdf works well: png and svg will raise error
g = ggplot(df, aes(x=:x1, y=:x2))+geom_point()
ggsave(joinpath(odir,"try.png"),g)
REvalError: Saving 7 x 7 in image
Warning in png_dev(..., res = dpi, units = "in") :
locale not supported by Xlib: some X ops will operate in C locale
Warning in png_dev(..., res = dpi, units = "in") :
X cannot set locale modifiers
Error in grid.Call(C_stringMetric, as.graphicsAnnot(x$label)) :
X11 font -adobe-helvetica-%s-%s-*-*-%d-*-*-*-*-*-*-*, face 1 at size 9 could not be loaded
Calls: <Anonymous> ... grid.Call -> <Anonymous> -> descentDetails.text -> grid.Call
Sup
Run corresponding codes in R works as well.
> library(ggplot2)
> df = data.frame(x1=rnorm(10),x2=rnorm(10))
> df
x1 x2
1 0.18165143 0.38032665
2 -0.62212533 0.52412366
3 0.98072899 0.30052532
4 -0.76721485 -0.63748290
5 0.00894366 0.04508702
6 -0.33166441 0.37056327
7 -0.14156795 -1.06334665
8 -1.08918837 -0.30631348
9 0.22035254 0.78816722
10 0.00356827 -0.62542425
> ggplot(df, aes(x=x1,y=x2))+geom_point()
And it generate pictures here:
Environments
R session
R version 4.1.1 (2021-08-10)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 18.04.3 LTS
Matrix products: default
BLAS: /mnt/Storage/home/yangdongxu/softwares/R/R_4.1_installed/lib/R/lib/libRblas.so
LAPACK: /mnt/Storage/home/yangdongxu/softwares/R/R_4.1_installed/lib/R/lib/libRlapack.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] ggplot2_3.3.5
loaded via a namespace (and not attached):
[1] magrittr_2.0.1 tidyselect_1.1.1 munsell_0.5.0 colorspace_2.0-2
[5] R6_2.5.1 rlang_0.4.12 fansi_0.5.0 dplyr_1.0.7
[9] grid_4.1.1 gtable_0.3.0 utf8_1.2.2 DBI_1.1.1
[13] withr_2.4.3 ellipsis_0.3.2 assertthat_0.2.1 digest_0.6.29
[17] tibble_3.1.6 lifecycle_1.0.1 crayon_1.4.2 purrr_0.3.4
[21] farver_2.1.0 vctrs_0.3.8 glue_1.5.1 labeling_0.4.2
[25] compiler_4.1.1 pillar_1.6.4 generics_0.1.1 scales_1.1.1
[29] pkgconfig_2.0.3
Julia: version 1.6.4
So what should I do to display the picture directly in jupyter like python %matplotlib inline?
Thanks.
I met some very strainge issue concerning with sqldf.
Example:
sqldf("select REGN, NII from dataframe ")
Even with very simple query this function returns an the following error:
Ошибка в result_create(conn#ptr, statement) :too many SQL variables
Here is the data sample I use as a result of dput(head(dataframe))
structure(list(REGN = c(1L, 21L, 23L, 52L, 53L, 55L), NII = c(5136380L,
30322L, 291812L, 92561L, 120618L, 140652L)), row.names = c(NA,
6L), class = "data.frame")
Edit:
But when I run the similar code to this dataframe:
structure(list(date_start = c("2008-04-01", "2016-04-01", "2019-04-01",
"2020-04-01", "2021-04-01"), date_end = c("2016-04-01", "2019-04-01",
"2020-04-01", "2021-04-01", "3000-01-01")), row.names = c(NA,
-5L), class = c("tbl_df", "tbl", "data.frame"))
everything works.
The results of sessioninfo():
R version 3.5.3 (2019-03-11)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19041)
Matrix products: default
locale:
[1] LC_COLLATE=Russian_Russia.1251
[2] LC_CTYPE=Russian_Russia.1251
[3] LC_MONETARY=Russian_Russia.1251
[4] LC_NUMERIC=C
[5] LC_TIME=Russian_Russia.1251
attached base packages:
[1] stats graphics grDevices utils datasets methods
[7] base
other attached packages:
[1] openxlsx_4.1.0 sqldf_0.4-11
[3] RSQLite_2.1.1 gsubfn_0.7
[5] proto_1.0.0 stringr_1.4.0
[7] reshape2_1.4.3 dplyr_0.8.0.1
[9] readxl_1.3.1 foreign_0.8-71
[11] RevoUtils_11.0.3 RevoUtilsMath_11.0.0
loaded via a namespace (and not attached):
[1] zip_2.0.1 Rcpp_1.0.1 cellranger_1.1.0
[4] pillar_1.3.1 compiler_3.5.3 plyr_1.8.4
[7] tools_3.5.3 RPostgres_1.1.1 digest_0.6.18
[10] bit_1.1-14 memoise_1.1.0 tibble_2.1.1
[13] pkgconfig_2.0.2 rlang_0.3.4 DBI_1.0.0
[16] rstudioapi_0.10 hms_0.4.2 bit64_0.9-7
[19] tidyselect_0.2.5 glue_1.3.1 R6_2.3.0
[22] tcltk_3.5.3 purrr_0.3.2 blob_1.1.1
[25] magrittr_1.5 assertthat_0.2.1 stringi_1.4.3
[28] chron_2.3-53 crayon_1.3.4
The results of ls():
[1] "complete" "con"
[3] "dateAn" "df"
[5] "df_3" "df_4"
[7] "df_inval" "df_inval_q"
[9] "df_itogo" "df_itogo_q"
[11] "df_itogo2" "df_rub"
[13] "df_rub_q" "df1"
[15] "f102_dates" "f102_maket"
[17] "f102_maket_1" "f102_maket_long"
[19] "f102_maket_long_symb" "i"
[21] "j" "k"
[23] "levelFunc" "listdbf"
[25] "m" "MainPath"
[27] "query_compos" "split"
[29] "subtract"
What's the matter?
There is a error in my code, can anyone help me please?
My code:
function funP(u, τ::Float64)
w = (τ*max(u, 0)) + ((1-τ)*max(-u, 0))
return w
end
τ = 0.2
modelquant = Model(with_optimizer(OSQP.Optimizer))
#variable(modelquant, β[i=0:1])
#variable(modelquant, erro[1:T])
#constraint(modelquant,[i=1:T], erro[i] >= contratos[i] - β[0] - β[1]*spot[i])
#constraint(modelquant,[i=1:T], erro[i] >= -contratos[i] + β[0] + β[1]*spot[i])
#objective(modelquant, Min, sum(funP(erro[i], τ) for i=1:T))
optimize!(modelquant)
objective_value(modelquant)
𝐁 = JuMP.value.(β)
The error is:
julia> #objective(modelquant, Min, sum(funP(erro[i], τ) for i=1:T))
ERROR: MethodError: no method matching isless(::Int64, ::VariableRef)
Closest candidates are:
isless(::Missing, ::Any) at missing.jl:87
isless(::Real, ::AbstractFloat) at operators.jl:166
isless(::Integer, ::ForwardDiff.Dual{Ty,V,N} where N where V) where Ty at C:\Users\Fernanda.julia\packages\ForwardDiff\kU1ce\src\dual.jl:140
...
Stacktrace:
[1] max(::VariableRef, ::Int64) at .\operators.jl:417
[2] funP(::VariableRef, ::Float64) at .\REPL[8]:2
[3] macro expansion at C:\Users\Fernanda.julia\packages\MutableArithmetics\bPWR4\src\rewrite.jl:276 [inlined]
[4] macro expansion at C:\Users\Fernanda.julia\packages\JuMP\qhoVb\src\macros.jl:830 [inlined]
[5] top-level scope at .\REPL[20]:1
Thank you so much!
You need to re-engineer your model to replace the max function with a binary variable.
In your case the code will look like this (check for typos):
#variable(modelquant, erro_neg[1:T], Bin)
#variable(modelquant, erro_pos[1:T], Bin)
#constraint(modelquant,for i=1:T,erro_neg[i]+erro_pos[i]==1)
#constraint(modelquant,for i=1:T,erro[i]*erro_pos[i] >= 0)
#constraint(modelquant,for i=1:T,erro[i]*erro_neg[i] <= 0)
#objective(modelquant, Min, sum( τ*erro_neg[i]*erro[i]+ (1-τ)*erro[i]*erro_npos[i] for i=1:T))
Please note that in my version you could actually safely remove the Bin condition from erro_neg and erro_pos and the model will still work (you need to test empirically what your solver prefers)
I can't seem to save chart_Series as pdf using the pdf() and dev.off() inside a for-loop. However, outside the for-loop if I run the code inside the hash box one at a time with incremental value of "i",I am able to produce the graphs. What am I doing wrong?
rm(list = ls(all = TRUE))
setwd("~/Documents/R")
library(tseries)
library(PerformanceAnalytics)
library(quantmod)
library(xts)
library(TTR)
library(Hmisc)
library(Quandl)
Quandl.api_key("yourKeyHere")
startDate = "2012-01-01"
symbols = c(
"ACAD",
"ACM" ,
"AL",
"ALB",
"AMD",
"AMKR",
"AVP",
"BC",
"BID",
"BKD",
"BWA" ,
"BYD" ,
"CAA" ,
"CAR" ,
"CAVM",
"CBL" ,
"CF" ,
"CHK" ,
"CIEN"
)
EOD <- function(symbols, startDate){
for (i in 1:length(symbols)){
stk <-Quandl(paste("EOD/",symbols[i],sep=""), start_date = startDate, type='xts')[,c(8,9,10,11,12)]
sp <-data.frame(Date=index(stk), round(coredata(stk), digits=3))
colnames(sp) <- c("Date","Open", "High", "Low", "Close", "Volume")
setwd("~/Documents/R/STK/csv/eq")
write.csv(sp, paste(paste0(symbols[i]),".csv", sep=""), row.names=FALSE)
}
}
EOD(symbols, startDate)
for (i in 1:length(symbols)){
setwd("~/Documents/R/STK/csv/eq")
stk1 <-getSymbols.csv(symbols[i], src="csv", from = startDate, col.names=c("Open","High","Low","Close","Volume"), auto.assign =FALSE)
colnames(stk1) <- c("Open", "High", "Low", "Close", "Volume")
##########################################################
setwd("~/Documents/R/STK/zs")
name <- paste0(symbols[i])
pdfname <- paste(name, ".pdf", sep="")
pdf(file=pdfname)
chart_Series(stk1 , subset = "2016-01-01::", name = paste0(symbols[i]))
dev.off()
##########################################################
}
######################################################
R version 3.3.2 (2016-10-31)
Platform: x86_64-apple-darwin13.4.0 (64-bit)
Running under: macOS Sierra 10.12.5
locale:
[1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] KFAS_1.2.8 Quandl_2.9.0 reshape2_1.4.2 Hmisc_4.0-3
[5] ggplot2_2.2.1 Formula_1.2-1 survival_2.41-3 quantstrat_0.9.1739
[9] foreach_1.4.3 blotter_0.9.1741 FinancialInstrument_1.2.0 quantmod_0.4-10
[13] TTR_0.23-1 PerformanceAnalytics_1.4.3541 xts_0.9-7 zoo_1.8-0
[17] tseries_0.10-41 timeSeries_3022.101.2 timeDate_3012.100 lattice_0.20-35
loaded via a namespace (and not attached):
[1] splines_3.3.2 colorspace_1.3-2 htmltools_0.3.6 mgcv_1.8-17 base64enc_0.1-3 rlang_0.1.1 foreign_0.8-69
[8] RColorBrewer_1.1-2 plyr_1.8.4 stringr_1.2.0 munsell_0.4.3 gtable_0.2.0 htmlwidgets_0.8 codetools_0.2-15
[15] labeling_0.3 latticeExtra_0.6-28 knitr_1.16 curl_2.6 htmlTable_1.9 Rcpp_0.12.11 acepack_1.4.1
[22] scales_0.4.1 backports_1.1.0 checkmate_1.8.2 jsonlite_1.5 gridExtra_2.2.1 digest_0.6.12 stringi_1.1.5
[29] grid_3.3.2 quadprog_1.5-5 tools_3.3.2 magrittr_1.5 lazyeval_0.2.0 tibble_1.3.3 cluster_2.0.6
[36] Matrix_1.2-10 data.table_1.10.4 httr_1.2.1 iterators_1.0.8 R6_2.2.2 rpart_4.1-11 nnet_7.3-12
[43] nlme_3.1-131