DATA MINING Desktop Survival Guide by Graham Williams
Desktop Survival Project Home Preface List of Figures List of Tables Process . Data Graphics in R Understanding Data Preparing Data Building Models Evaluating Models Algorithms Apriori Bagging Bayes Classifier Boosting Conditional Trees Decision Trees Hierarchical Clustering Kernel Methods K-Means K-Nearest Neighbours Linear Models Logistic Regression Neural Networks Support Vector Machines Text Mining Open Products Borgelt Data Mining Suite R Rattle Weka Closed Products C4.5 Clementine Enterprise Miner Equbits Foresight GhostMiner InductionEngine ODM Statistica Data Miner TreeNet Virtual Predict Appendicies Glossary Bibliography Index

Garbage Collection

When doing timings of commands it is useful to know that garbage collection plays a role. R adjusts its garbage collection triggers accoring to your usage. When you first start using large objects the trigger levels will grow and generally things will speed up. You can use gcinfo to see the adjustments in action:

> gcinfo(TRUE)

For the system.time function use the gcFirst.

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