classifly: Explore classification models in high dimensions

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Given $p$-dimensional training data containing $d$ groups (the design space), a classification algorithm (classifier) predicts which group new data belongs to. Generally the input to these algorithms is high dimensional, and the boundaries between groups will be high dimensional and perhaps curvilinear or multi-faceted. This package implements methods for understanding the division of space between the groups.

Author
Hadley Wickham <h.wickham@gmail.com>
Date of publication
2014-04-23 19:51:22
Maintainer
Hadley Wickham <h.wickham@gmail.com>
License
MIT + file LICENSE
Version
0.4
URLs

View on CRAN

Man pages

advantage
Calculate the advantage the most likely class has over the...
classifly
Classifly provides a convenient method to fit a...
classify
Extract classifications from a variety of methods.
explore
Default method for exploring objects
generate_classification_data
Generate classification data.
generate_data
Generate new data from a data frame.
knnf
A wrapper function for 'knn' to allow use with classifly.
olives
Olives
posterior
Extract posterior group probabilities
simvar
Simulate observations from a vector
variables
Extract predictor and response variables for a model object.

Files in this package

classifly
classifly/NAMESPACE
classifly/CHANGELOG
classifly/NEWS
classifly/data
classifly/data/olives.tab
classifly/R
classifly/R/rescaler.R
classifly/R/classification.r
classifly/R/olives.R
classifly/R/explore.r
classifly/R/data.r
classifly/R/knn.r
classifly/MD5
classifly/DESCRIPTION
classifly/man
classifly/man/explore.Rd
classifly/man/olives.Rd
classifly/man/classify.Rd
classifly/man/classifly.Rd
classifly/man/simvar.Rd
classifly/man/variables.Rd
classifly/man/advantage.Rd
classifly/man/generate_data.Rd
classifly/man/posterior.Rd
classifly/man/generate_classification_data.Rd
classifly/man/knnf.Rd
classifly/LICENSE