Functions and Data for the Second Edition of "Data Mining with R"
The solutions for the test data set for predicting algae blooms
Fill in NA values with central statistics
Obtain statistic of centrality
Creates an embeded data set from an univariate time series
An auxiliary function of lofactor()
Functions and data for the second edition of the book "Data Mining wit...
k-Nearest Neighbour Classification
An auxiliary function of lofactor()
Fill in NA values with the values of the nearest neighbours
An implementation of the LOF algorithm
Find rows with too many NA values
Counts the number of lines of a file
Obtain outlier rankings
An auxiliary function of lofactor()
Obtain a tree-based model
Prune a tree-based model using the SE rule
Drawing a random sample of lines from a CSV file
Drawing a random sample of records of a table stored in a DBMS
Self train a model on semi-supervised data
Precision and recall of a set of predicted trading signals
Normalize a set of continuous values using SoftMax
A set of daily quotes for SP500 in CSV Format
Testing data for predicting algae blooms
Class "tradeRecord"
Discretize a set of values into a set of trading signals
Simulate daily trading using a set of trading signals
Obtain a set of evaluation metrics for a set of trading actions
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.