Functions and data accompanying the second edition of the book "Data Mining with R, learning with case studies" by Luis Torgo, published by CRC Press.
|Author||Luis Torgo [aut, cre]|
|Date of publication||2016-10-13 00:23:37|
|Maintainer||Luis Torgo <firstname.lastname@example.org>|
|License||GPL (>= 2)|
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