R
-
**Which versions of R are compatible with H2O?**
Currently, the only version of R that is known to not work well with H2O
is R version 3.1.0 (codename "Spring Dance"). If you are using this
version, we recommend upgrading the R version before using H2O.
--------------
**What R packages are required to use H2O?**
The following packages are required:
- ``methods``
- ``statmod``
- ``stats``
- ``graphics``
- ``RCurl``
- ``jsonlite``
- ``tools``
- ``utils``
Some of these packages have dependencies; for example, ``bitops`` is
required, but it is a dependency of the ``RCurl`` package, so ``bitops``
is automatically included when ``RCurl`` is installed.
If you are encountering errors related to missing R packages when using
H2O, refer to the following list for a complete list of all R packages,
including dependencies:
- ``statmod``
- ``bitops``
- ``RCurl``
- ``jsonlite``
- ``methods``
- ``stats``
- ``graphics``
- ``tools``
- ``utils``
- ``stringi``
- ``magrittr``
- ``colorspace``
- ``stringr``
- ``RColorBrewer``
- ``dichromat``
- ``munsell``
- ``labeling``
- ``plyr``
- ``digest``
- ``gtable``
- ``reshape2``
- ``scales``
- ``proto``
- ``ggplot2``
- ``h2oEnsemble``
- ``gtools``
- ``gdata``
- ``caTools``
- ``gplots``
- ``chron``
- ``ROCR``
- ``data.table``
- ``cvAUC``
Finally, if you are running R on Linux, then you must install ``libcurl``, which allows H2O to communicate with R.
--------------
**How can I install the H2O R package if I am having permissions
problems?**
This issue typically occurs for Linux users when the R software was
installed by a root user. For more information, refer to the following
`link <https://stat.ethz.ch/R-manual/R-devel/library/base/html/libPaths.html>`__.
To specify the installation location for the R packages, create a file
that contains the ``R_LIBS_USER`` environment variable:
``echo R_LIBS_USER=\"~/.Rlibrary\" > ~/.Renviron``
Confirm the file was created successfully using ``cat``:
``$ cat ~/.Renviron``
You should see the following output:
``R_LIBS_USER="~/.Rlibrary"``
Create a new directory for the environment variable:
``$ mkdir ~/.Rlibrary``
Start R and enter the following:
``.libPaths()``
Look for the following output to confirm the changes:
::
[1] "<Your home directory>/.Rlibrary"
[2] "/Library/Frameworks/R.framework/Versions/3.1/Resources/library"
--------------
**I received the following error message after launching H2O in RStudio
and using ``h2o.init`` - what should I do to resolve this error?**
::
Error in h2o.init() :
Version mismatch! H2O is running version 3.2.0.9 but R package is version 3.2.0.3
This error is due to a version mismatch between the H2O R package and
the running H2O instance. Make sure you are using the latest version of
both files by downloading H2O from the `downloads
page <http://h2o.ai/download/>`__ and installing the latest version and
that you have removed any previous H2O R package versions by running:
::
if ("package:h2o" %in% search()) { detach("package:h2o", unload=TRUE) }
if ("h2o" %in% rownames(installed.packages())) { remove.packages("h2o") }
Make sure to install the dependencies for the H2O R package as well:
::
if (! ("methods" %in% rownames(installed.packages()))) { install.packages("methods") }
if (! ("statmod" %in% rownames(installed.packages()))) { install.packages("statmod") }
if (! ("stats" %in% rownames(installed.packages()))) { install.packages("stats") }
if (! ("graphics" %in% rownames(installed.packages()))) { install.packages("graphics") }
if (! ("RCurl" %in% rownames(installed.packages()))) { install.packages("RCurl") }
if (! ("jsonlite" %in% rownames(installed.packages()))) { install.packages("jsonlite") }
if (! ("tools" %in% rownames(installed.packages()))) { install.packages("tools") }
if (! ("utils" %in% rownames(installed.packages()))) { install.packages("utils") }
Finally, install the latest stable version of the H2O package for R:
::
install.packages("h2o", type="source", repos=(c("http://h2o-release.s3.amazonaws.com/h2o/latest_stable_R)))
library(h2o)
localH2O = h2o.init()
If your R version is older than the H2O R package, upgrade your R version using ``update.packages(checkBuilt=TRUE, ask=FALSE)``.
--------------
**I received the following error message after launching H2O in RStudio
and using ``h2o.init`` - what should I do to resolve this error?**
::
Server error - server 127.0.0.1 is unreachable at this moment.
Please retry the request or contact your administrator.
This error occurs when the proxy is set in your R environment. The resolution is to unset that so that you can access localhost from within R. Run the following to unset the proxy:
::
Sys.unsetenv("http_proxy")
Sys.unsetenv("https_proxy")
Sys.unsetenv("http_proxy_user")
Sys.unsetenv("https_proxy_user")
--------------
**I received the following error message after trying to run some code -
what should I do?**
::
> fit <- h2o.deeplearning(x=2:4, y=1, training_frame=train_hex)
|=========================================================================================================| 100%
Error in model$training_metrics$MSE :
$ operator not defined for this S4 class
In addition: Warning message:
Not all shim outputs are fully supported, please see ?h2o.shim for more information
Remove the ``h2o.shim(enable=TRUE)`` line and try running the code
again. Note that the ``h2o.shim`` is only a way to notify users of
previous versions of H2O about changes to the H2O R package - it will
not revise your code, but provides suggested replacements for deprecated
commands and parameters.
--------------
**How do I extract the model weights from a model I've creating using
H2O in R? I've enabled ``extract_model_weights_and_biases``, but the
output refers to a file I can't open in R.**
For an example of how to extract weights and biases from a model, refer
to the following repo location on
`GitHub <https://github.com/h2oai/h2o-3/blob/master/h2o-r/tests/testdir_algos/deeplearning/runit_deeplearning_weights_and_biases.R>`__.
--------------
**How do I extract the run time of my model as output?**
For the following example:
::
out.h2o.rf = h2o.randomForest( x=c("x1", "x2", "x3", "w"), y="y", training_frame=h2o.df.train, seed=555, model_id= "my.model.1st.try.out.h2o.rf" )
Use ``out.h2o.rf@model$run_time`` to determine the value of the
``run_time`` variable.
--------------
**What is the best way to do group summarizations? For example, getting
sums of specific columns grouped by a categorical column.**
We strongly recommend using ``h2o.group_by`` for this function instead
of ``h2o.ddply``, as shown in the following example:
::
newframe <- h2o.group_by(h2oframe, by="footwear_category", nrow("email_event_click_ct"), sum("email_event_click_ct"), mean("email_event_click_ct"), sd("email_event_click_ct"), gb.control = list( col.names=c("count", "total_email_event_click_ct", "avg_email_event_click_ct", "std_email_event_click_ct") ) )
Using ``gb.control`` is optional; here it is included so the column
names are user-configurable.
The ``by`` option can take a list of columns if you want to group by
more than one column to compute the summary as shown in the following
example:
::
newframe <- h2o.group_by(h2oframe, by=c("footwear_category","age_group"), nrow("email_event_click_ct"), sum("email_event_click_ct"), mean("email_event_click_ct"), sd("email_event_click_ct"), gb.control = list( col.names=c("count", "total_email_event_click_ct", "avg_email_event_click_ct", "std_email_event_click_ct") ) )
--------------
**I'm using Linux and I want to run H2O in R - are there any
dependencies I need to install?**
Yes, make sure to install ``libcurl``, which allows H2O to communicate
with R. We also recommend disabling SElinux and any firewalls, at least
initially until you have confirmed H2O can initialize.
- On Ubuntu, run: ``apt-get install libcurl4-openssl-dev``
- On CentOS, run: ``yum install libcurl-devel``
--------------
**How do I change variable/header names on an H2O frame in R?**
There are two ways to change header names. To specify the headers during
parsing, import the headers in R and then specify the header as the
column name when the actual data frame is imported:
::
header <- h2o.importFile(path = pathToHeader)
data <- h2o.importFile(path = pathToData, col.names = header)
data
You can also use the ``names()`` function:
::
header <- c("user", "specified", "column", "names")
data <- h2o.importFile(path = pathToData)
names(data) <- header
To replace specific column names, you can also use a ``sub/gsub`` in R:
::
header <- c("user", "specified", "column", "names")
## I want to replace "user" column with "computer"
data <- h2o.importFile(path = pathToData)
names(data) <- sub(pattern = "user", replacement = "computer", x = names(header))
--------------
**My R terminal crashed - how can I re-access my H2O frame?**
Launch H2O and use your web browser to access the web UI, Flow, at
``localhost:54321``. Click the **Data** menu, then click **List All
Frames**. Copy the frame ID, then run ``h2o.ls()`` in R to list all the
frames, or use the frame ID in the following code (replacing
``YOUR_FRAME_ID`` with the frame ID):
::
library(h2o)
localH2O = h2o.init(ip="sri.h2o.ai", port=54321, startH2O = F, strict_version_check=T)
data_frame <- h2o.getFrame(frame_id = "YOUR_FRAME_ID")
--------------
**How do I remove rows containing NAs in an H2OFrame?**
To remove NAs from rows:
::
a b c d e
1 0 NA NA NA NA
2 0 2 2 2 2
3 0 NA NA NA NA
4 0 NA NA 1 2
5 0 NA NA NA NA
6 0 1 2 3 2
Removing rows 1, 3, 4, 5 to get:
::
a b c d e
2 0 2 2 2 2
6 0 1 2 3 2
Use ``na.omit(myFrame)``, where ``myFrame`` represents the name of the
frame you are editing.
--------------
**I installed H2O in R using OS X and updated all the dependencies, but
the following error message displayed:
``Error in .h2o.doSafeREST(h2oRestApiVersion = h2oRestApiVersion, Unexpected CURL error: Empty reply from server``
- what should I do?**
This error message displays if the ``JAVA_HOME`` environment variable is
not set correctly. The ``JAVA_HOME`` variable is likely points to Apple
Java version 6 instead of Oracle Java version 8.
If you are running OS X 10.7 or earlier, enter the following in
Terminal:
``export JAVA_HOME=/Library/Internet\ Plug-Ins/JavaAppletPlugin.plugin/Contents/Home``
If you are running OS X 10.8 or later, modify the launchd.plist by
entering the following in Terminal:
::
cat << EOF | sudo tee /Library/LaunchDaemons/setenv.JAVA_HOME.plist
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
<key>Label</key>
<string>setenv.JAVA_HOME</string>
<key>ProgramArguments</key>
<array>
<string>/bin/launchctl</string>
<string>setenv</string>
<string>JAVA_HOME</string>
<string>/Library/Internet Plug-Ins/JavaAppletPlugin.plugin/Contents/Home</string>
</array>
<key>RunAtLoad</key>
<true/>
<key>ServiceIPC</key>
<false/>
</dict>
</plist>
EOF
--------------
.. raw:: html
<!---
in progress - commenting out until complete
**How do I extract the variable importance from the output in R?**
Launch R, then enter the following:
```
library(h2o)
h <- h2o.init()
as.h2o(iris)
as.h2o(testing)
m <- h2o.gbm(x=1:4, y=5, data=hex, importance=T)
m@model$varimp
Relative importance Scaled.Values Percent.Influence
Petal.Width 7.216290000 1.0000000000 51.22833426
Petal.Length 6.851120500 0.9493965043 48.63600147
Sepal.Length 0.013625654 0.0018881799 0.09672831
Sepal.Width 0.005484723 0.0007600474 0.03893596
```
The variable importances are returned as an R data frame and you can extract the names and values of the data frame as follows:
```
is.data.frame(m@model$varimp)
# [1] TRUE
names(m@model$varimp)
# [1] "Relative importance" "Scaled.Values" "Percent.Influence"
rownames(m@model$varimp)
# [1] "Petal.Width" "Petal.Length" "Sepal.Length" "Sepal.Width"
m@model$varimp$"Relative importance"
# [1] 7.216290000 6.851120500 0.013625654 0.005484723
```
-->
--------------
**How does the ``col.names`` argument work in ``group_by``?**
You need to add the ``col.names`` inside the ``gb.control`` list. Refer
to the following example:
::
newframe <- h2o.group_by(dd, by="footwear_category", nrow("email_event_click_ct"), sum("email_event_click_ct"), mean("email_event_click_ct"),
sd("email_event_click_ct"), gb.control = list( col.names=c("count", "total_email_event_click_ct", "avg_email_event_click_ct", "std_email_event_click_ct") ) )
newframe$avg_email_event_click_ct2 = newframe$total_email_event_click_ct / newframe$count
--------------
**How are the results of ``h2o.predict`` displayed?**
The order of the rows in the results for ``h2o.predict`` is the same as
the order in which the data was loaded, even if some rows fail (for
example, due to missing values or unseen factor levels). To bind a
per-row identifier, use ``cbind``.
--------------
**How do I view all the variable importances for a model?**
By default, H2O returns the top five and lowest five variable
importances. To view all the variable importances, use the following:
::
model <- h2o.getModel(model_id = "my_H2O_modelID",conn=localH2O)
varimp<-as.data.frame(h2o.varimp(model))
--------------
**How do I add random noise to a column in an H2O frame?**
To add random noise to a column in an H2O frame, refer to the following
example:
::
h2o.init()
fr <- as.h2o(iris)
|======================================================================| 100%
random_column <- h2o.runif(fr)
new_fr <- h2o.cbind(fr,random_column)
new_fr