DATA MINING Desktop Survival Guide by Graham Williams
Desktop Survival Project Home List of Figures List of Tables Data Mining Data Mining Data Mining with Rattle Introduction Data Transform Explore A Model Building Framework Unsupervised Modelling Two Class Models Multi Class Models Regression Models Text Mining Evaluation and Deployment Moving into R Troubleshooting R for the Data Miner R Data Graphics in R Understanding Data Preparing Data Building Models Evaluating Models Algorithms Apriori Bagging Bayes Classifier Boosting Cluster Analysis Conditional Trees Hierarchical Clustering K-Means K-Nearest Neighbours Linear Models Logistic Regression Neural Networks Support Vector Machines Text Mining Open Products AlphaMiner Borgelt Data Mining Suite KNime R Rattle Weka Closed Products C4.5 Clementine Equbits Foresight GhostMiner InductionEngine ODM Enterprise Miner Statistica Data Miner TreeNet Virtual Predict Appendicies Glossary Bibliography Index

Evaluation

R is an http://en.wikipedia.org/wiki/Interpreted_Languageinterpreted language providing procedural, http://en.wikipedia.org/wiki/Functional_languagefunctional, and object oriented paradigms. The basic mode of interacting with R has the user typing commands (function names and arguments) and R evaluating them to return an answer (or an object). The object returned is often a vector (a collection of objects all of the same data type). The elements of the vector are numbered, beginning with 1, as indicated within the square brackets of the output. The returned elements are printed at the beginning of the line following the commands you type, but for brevity we include them as comments in our examples here (a comment is introduced with a # and continues to the end of a line):

> 5+2	                # [1] 7
> 5-2			# [1] 3
> 5*2			# [1] 10
> 5/2			# [1] 2.5
> 5%%2			# [1] 1     Remainder after division
> 5^2			# [1] 25
> 5^2-2*3		# (5^2) - (2*3)      [1] 19

All of these examples use in place function names (i.e., operators like + and -) with the arguments on either side and returns a vector of length 1.

Documentation relating to operator precedence is available with:

> help(Syntax)

R is most typically seen as a http://en.wikipedia.org/wiki/Functional_programmingfunctional language, meaning that it works by calling functions, such as log (for calculating the logarithm of a number), and returning values from these functions. Functions often require arguments that give additional information to the function. Some arguments are optional, and can be introduced through giving the name of the argument, which can be abbreviated, or missing altogether using the position to indicate the intent of the argument.

> log(1000)		# 6.907755
> log(1000, base=10)	# 3
> log(1000, b=10)	# 3 Command arguments can be abbreviated
> log(1000, 10)		# 3 Command arguments can be positional

In fact, even the in-place operators we saw above (e.g., 5+2) are just a syntactic abbreviation for a function call:

> "+"(5,2)    # 7 In-place operators are a syntactic convenience

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