h2o
#insatlling h2o packages
install.packages("h2o")Installing package into ‘/cloud/lib/x86_64-pc-linux-gnu-library/4.4’
(as ‘lib’ is unspecified)
trying URL 'http://rspm/default/__linux__/focal/latest/src/contrib/h2o_3.44.0.3.tar.gz'
Content type 'application/x-gzip' length 266595032 bytes (254.2 MB)
==================================================
downloaded 254.2 MB
* installing *binary* package ‘h2o’ ...
* DONE (h2o)
The downloaded source packages are in
‘/tmp/RtmpAuBFVr/downloaded_packages’#Let's us see if the installation worked
library(h2o)
----------------------------------------------------------------------
Your next step is to start H2O:
> h2o.init()
For H2O package documentation, ask for help:
> ??h2o
After starting H2O, you can use the Web UI at http://localhost:54321
For more information visit https://docs.h2o.ai
----------------------------------------------------------------------
Attaching package: ‘h2o’
The following objects are masked from ‘package:stats’:
cor, sd, var
The following objects are masked from ‘package:base’:
&&, %*%, %in%, ||, apply, as.factor, as.numeric, colnames, colnames<-, ifelse,
is.character, is.factor, is.numeric, log, log10, log1p, log2, round, signif, trunc#
h2o.init()
H2O is not running yet, starting it now...
Note: In case of errors look at the following log files:
/tmp/RtmpAuBFVr/file14e26350bec/h2o_r2168188_started_from_r.out
/tmp/RtmpAuBFVr/file14e4fb4a4a8/h2o_r2168188_started_from_r.erropenjdk version "11.0.22" 2024-01-16
OpenJDK Runtime Environment (build 11.0.22+7-post-Ubuntu-0ubuntu220.04.1)
OpenJDK 64-Bit Server VM (build 11.0.22+7-post-Ubuntu-0ubuntu220.04.1, mixed mode, sharing)
Starting H2O JVM and connecting: ... Connection successful!
R is connected to the H2O cluster:
H2O cluster uptime: 2 seconds 764 milliseconds
H2O cluster timezone: UTC
H2O data parsing timezone: UTC
H2O cluster version: 3.44.0.3
H2O cluster version age: 1 year, 1 month and 14 days
H2O cluster name: H2O_started_from_R_r2168188_eng994
H2O cluster total nodes: 1
H2O cluster total memory: 0.24 GB
H2O cluster total cores: 1
H2O cluster allowed cores: 1
H2O cluster healthy: TRUE
H2O Connection ip: localhost
H2O Connection port: 54321
H2O Connection proxy: NA
H2O Internal Security: FALSE
R Version: R version 4.4.2 (2024-10-31) Warning in h2o.clusterInfo() :
Your H2O cluster version is (1 year, 1 month and 14 days) old. There may be a newer version available.
Please download and install the latest version from: https://h2o-release.s3.amazonaws.com/h2o/latest_stable.html??h20#use local host 5431
# We use an h2o cluster on the specified port 5431. We use localhost and port 5431
h2o.init(ip = "localhost", port = 5431)#Next step is to start h2o cluster
h2o.init() Connection successful!
R is connected to the H2O cluster:
H2O cluster uptime: 7 minutes 56 seconds
H2O cluster timezone: UTC
H2O data parsing timezone: UTC
H2O cluster version: 3.44.0.3
H2O cluster version age: 1 year, 1 month and 14 days
H2O cluster name: H2O_started_from_R_r2168188_end099
H2O cluster total nodes: 1
H2O cluster total memory: 0.18 GB
H2O cluster total cores: 1
H2O cluster allowed cores: 1
H2O cluster healthy: TRUE
H2O Connection ip: localhost
H2O Connection port: 54321
H2O Connection proxy: NA
H2O Internal Security: FALSE
R Version: R version 4.4.2 (2024-10-31) Warning in h2o.clusterInfo() :
Your H2O cluster version is (1 year, 1 month and 14 days) old. There may be a newer version available.
Please download and install the latest version from: https://h2o-release.s3.amazonaws.com/h2o/latest_stable.htmllibrary(h2o)
#This command is used to initialize the h2o cluster with the specified number of threads for parallel processing
h2o.init(nthreads=-1) Connection successful!
R is connected to the H2O cluster:
H2O cluster uptime: 9 seconds 778 milliseconds
H2O cluster timezone: UTC
H2O data parsing timezone: UTC
H2O cluster version: 3.44.0.3
H2O cluster version age: 1 year, 1 month and 14 days
H2O cluster name: H2O_started_from_R_r2168188_eng994
H2O cluster total nodes: 1
H2O cluster total memory: 0.23 GB
H2O cluster total cores: 1
H2O cluster allowed cores: 1
H2O cluster healthy: TRUE
H2O Connection ip: localhost
H2O Connection port: 54321
H2O Connection proxy: NA
H2O Internal Security: FALSE
R Version: R version 4.4.2 (2024-10-31) Warning in h2o.clusterInfo() :
Your H2O cluster version is (1 year, 1 month and 14 days) old. There may be a newer version available.
Please download and install the latest version from: https://h2o-release.s3.amazonaws.com/h2o/latest_stable.html#here we are importing dataset that is built in h20
datasets <- "https://raw.githubusercontent.com/DarrenCook/h2o/bk/datasets/"
data <- h2o.importFile(paste0(datasets, "iris_wheader.csv"))y <- "class"
x <- setdiff(names(data), y)
parts <- h2o.splitFrame(data, 0.8)
train <- parts[[1]]
test <- parts[[2]]
m <- h2o.deeplearning(x, y, train)
|
| | 0%
|
|==============================================================================================| 100%#This function is used in teh contact of statistical modelinh and machine learning.
p <- h2o.predict(m, test)h2o.mse(m)#this deeplearning model that we used in this platform is built in and struggles to show the Iris vs vaeriscolor
h2o.confusionMatrix(m)#The "predict" column in the first row shows the predicted class for the test data, while the other three columns display its confidence. It's very confident it’s a setosa, but less certain about the other predictions.
as.data.frame(p)#The correct species is in test_class, while H2O’s model's prediction is in deeplearning’s guess, predict.
as.data.frame( h2o.cbind(p$predict, test$class) )
#We can analyze the model's accuracy by calculating mean(predict == testclass) in R, which gives 0.90625. This means the model correctly predicted 90.6% of the 30 test samples.
mean(p$predict ==test$class)Error: object 'p' not found#Another way to find the accuracy is by using h2o.performance(m, test) in R instead of predict().
h2o.performance(m,test)