Functions and data for "Data Mining with R"

algae | Training data for predicting algae blooms |

algae.sols | The solutions for the test data set for predicting algae... |

bestScores | Obtain the best scores from an experimental comparison |

bootRun-class | Class "bootRun" |

bootSettings-class | Class "bootSettings" |

bootstrap | Runs a bootstrap experiment |

centralImputation | Fill in NA values with central statistics |

centralValue | Obtain statistic of centrality |

class.eval | Calculate Some Standard Classification Evaluation Statistics |

compAnalysis | Analyse and print the statistical significance of the... |

compExp-class | Class "compExp" |

CRchart | Plot a Cumulative Recall chart |

crossValidation | Run a Cross Validation Experiment |

cvRun-class | Class "cvRun" |

cvSettings-class | Class "cvSettings" |

dataset-class | Class "dataset" |

dist.to.knn | An auxiliary function of 'lofactor()' |

DMwR-defunct | Defunct Functions in Package 'DMwR' |

DMwR-package | Functions and data for the book "Data Mining with R" |

dsNames | Obtain the name of the data sets involved in an experimental... |

experimentalComparison | Carry out Experimental Comparisons Among Learning Systems |

expSettings-class | Class "expSettings" |

getFoldsResults | Obtain the results on each iteration of a learner |

getSummaryResults | Obtain a set of descriptive statistics of the results of a... |

getVariant | Obtain the learner associated with an identifier within a... |

growingWindowTest | Obtain the predictions of a model using a growing window... |

GSPC | A set of daily quotes for SP500 |

hldRun-class | Class "hldRun" |

hldSettings-class | Class "hldSettings" |

holdOut | Runs a Hold Out experiment |

join | Merging several 'compExp' class objects |

kNN | k-Nearest Neighbour Classification |

knneigh.vect | An auxiliary function of 'lofactor()' |

knnImputation | Fill in NA values with the values of the nearest neighbours |

learner-class | Class "learner" |

learnerNames | Obtain the name of the learning systems involved in an... |

LinearScaling | Normalize a set of continuous values using a linear scaling |

lofactor | An implementation of the LOF algorithm |

loocv | Run a Leave One Out Cross Validation Experiment |

loocvRun-class | Class "loocvRun" |

loocvSettings-class | Class "loocvSettings" |

manyNAs | Find rows with too many NA values |

mcRun-class | Class "mcRun" |

mcSettings-class | Class "mcSettings" |

monteCarlo | Run a Monte Carlo experiment |

outliers.ranking | Obtain outlier rankings |

PRcurve | Plot a Precision/Recall curve |

prettyTree | Visual representation of a tree-based model |

rankSystems | Provide a ranking of learners involved in an experimental... |

reachability | An auxiliary function of 'lofactor()' |

regr.eval | Calculate Some Standard Regression Evaluation Statistics |

ReScaling | Re-scales a set of continuous values into a new range using a... |

resp | Obtain the target variable values of a prediction problem |

rpartXse | Obtain a tree-based model |

rt.prune | Prune a tree-based model using the SE rule |

runLearner | Run a Learning Algorithm |

sales | A data set with sale transaction reports |

SelfTrain | Self train a model on semi-supervised data |

sigs.PR | Precision and recall of a set of predicted trading signals |

slidingWindowTest | Obtain the predictions of a model using a sliding window... |

SMOTE | SMOTE algorithm for unbalanced classification problems |

SoftMax | Normalize a set of continuous values using SoftMax |

statNames | Obtain the name of the statistics involved in an experimental... |

statScores | Obtains a summary statistic of one of the evaluation metrics... |

subset-methods | Methods for Function subset in Package 'DMwR' |

task-class | Class "task" |

test.algae | Testing data for predicting algae blooms |

tradeRecord-class | Class "tradeRecord" |

tradingEvaluation | Obtain a set of evaluation metrics for a set of trading... |

trading.signals | Discretize a set of values into a set of trading signals |

trading.simulator | Simulate daily trading using a set of trading signals |

ts.eval | Calculate Some Standard Evaluation Statistics for Time Series... |

unscale | Invert the effect of the scale function |

variants | Generate variants of a learning system |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.