Functions and Data for the Second Edition of "Data Mining with R"

algae | Training data for predicting algae blooms |

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

centralImputation | Fill in NA values with central statistics |

centralValue | Obtain statistic of centrality |

createEmbedDS | Creates an embeded data set from an univariate time series |

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

DMwR2-package | Functions and data for the second edition of the book "Data... |

GSPC | A set of daily quotes for SP500 |

kNN | k-Nearest Neighbour Classification |

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

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

lofactor | An implementation of the LOF algorithm |

manyNAs | Find rows with too many NA values |

nrLinesFile | Counts the number of lines of a file |

outliers.ranking | Obtain outlier rankings |

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

rpartXse | Obtain a tree-based model |

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

sales | A data set with sale transaction reports |

sampleCSV | Drawing a random sample of lines from a CSV file |

sampleDBMS | Drawing a random sample of records of a table stored in a... |

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

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

SoftMax | Normalize a set of continuous values using SoftMax |

sp500 | A set of daily quotes for SP500 in CSV Format |

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 |

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