Statistical Learning and Visualization
You can classify and identify features in data sets, set up cross-validation experiments, and compare different classification methods.
The toolbox provides functions that build on the classification
and statistical learning tools in the Statistics and Machine Learning Toolbox™ software
(classify
, kmeans
, fitctree
, and fitrtree
).
These functions include imputation tools (knnimpute
), and K-nearest neighbor classifiers (fitcknn
).
Other functions include set up of cross-validation experiments
(crossvalind
) and comparison
of the performance of different classification methods (classperf
). In addition, there are tools
for selecting diversity and discriminating features (rankfeatures
, randfeatures
).