Description Usage Arguments Value Examples
the matrix containing the elementary error estimators. Their rows correspond to the learning sets, and columns correspond to the test chunks.
1 2 | errorMatrix(learningAlgorithm, drawFunction, g, testChunkSize, Nwithin = 110,
Nbetween = 100, ...)
|
learningAlgorithm |
a function that takes learning data as argument and outputs a prediction rule in the form of another function that maps test data to numeric vectors. These can be errors or AUCs, one for each testing data set. |
drawFunction |
a function that returns a dataframe with the response variable in a column names y |
g |
the learning sample sizelearningAlgorithm, drawFunction, Nwithin=12, Nbetween=17) |
testChunkSize |
the sample size of a single test chunk |
Nwithin |
number of test chunks to be drawn for each training iteration. In the paper, this number was called n_test. Defaults to 110. |
Nbetween |
number of training data sets to be drawn. In the paper, this number was calles N. Defaults to 100. |
... |
additional parameters to be passed to the drawing function |
the error matrix
1 2 3 4 5 6 | errorMatrix(
learningAlgorithm=svmLearning,
drawFunction=drawLogit,
g=20,
testChunkSize=1
)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.