Description Usage Arguments Value Author(s) Examples
To get (back) to the overview of all steps and functions use this link:
a.a.main
This is a wrapper function for classifying data with support vector machines
It executes these functions:
g.b.step1
g.c.step2
1 | g.a.svm.start(block, feature1, saveFile, classLabel, feature2 = NULL)
|
block |
A string that holds a path to a cross-validation block file |
feature1 |
A string that holds a path to a feature data file (hog or colorHist) |
saveFile |
A string that holds a path to which the result should be stored as .rda file. |
classLabel |
A string that holds a path to a file with classification labels for the feature data |
feature2 |
A string that holds a path to a second feature data file (the type that was not used in |
A table that holds the pairs of correct and not correct predicted images, the number of correct predicted images and the accuracy percentage
Colin Juers
1 2 3 | \code{result <- d.a.randomForest.start("data/blocks2677IMG.rda", "data/hog_original_8_9_complete.rda",
"data/colorHistRGBNorm_original_255buckets_hog_original_8_9_nodes7_svm_result.rda", "data/classesOrig.rda",
100, feature2 = "data/colorHistOriginalRGBNorm255Buckets.rda")}
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