R package for Machine Learning - caret

The most trending topics these days are Artificial Intelligence and Machine Learning. Every day you get tons of news about AI and ML. R programming language is well placed to initiate you into these 'esoteric' topics. There is a learning curve and should you learn to scale the peaks there will be rewards. So much of 'carrot' talk.

In R, the package that does a lot of work for you as far as AI and ML are concerned is the package 'caret'. You should load this package and use its library to begin your AI/ML related activities. Of course there are more roads to Rome than one.

If have been working with R, you can launch R and install the package. If you are using Microsoft R (R Server/ R Client), you can launch the R GUI.

Run the install statement ass shown:

> install.packages("caret")

Installing package into ‘C:/Users/Owner/Documents/R/win-library/3.3’

(as ‘lib’ is unspecified)

also installing the dependencies ‘minqa’, ‘nloptr’, ‘RcppEigen’, ‘lme4’, ‘SparseM’, ‘MatrixModels’, ‘pbkrtest’, ‘quantreg’, ‘car’

After contacting the site to download a number of packages are downloaded and checked as shown here:

package ‘minqa’ successfully unpacked and MD5 sums checked

package ‘nloptr’ successfully unpacked and MD5 sums checked

package ‘RcppEigen’ successfully unpacked and MD5 sums checked

package ‘lme4’ successfully unpacked and MD5 sums checked

package ‘SparseM’ successfully unpacked and MD5 sums checked

package ‘MatrixModels’ successfully unpacked and MD5 sums checked

package ‘pbkrtest’ successfully unpacked and MD5 sums checked

package ‘quantreg’ successfully unpacked and MD5 sums checked

package ‘car’ successfully unpacked and MD5 sums checked

package ‘caret’ successfully unpacked and MD5 sums checked

Note that the 'caret' library requires ggplot2 which will also be loaded, if you already have it.

Please look up other R related posts on this blog:

http://hodentekhelp.blogspot.com/search?q=ggplot

Let us come back and look at how it may be used.

As is, this post is not 100% SQL Server except that I used the Microsoft R for this post.