Classifiers – Various
nbayesc | Bayes classifier for given normal densities | more routines |
mogc | Mixture of gaussians classification | |
knnc | k-nearest neighbour classifier (find k, build classifier) | |
statsknnc | Statistical toolbox nearest neighbor classifier | |
parzenc | Parzen classifier | |
parzendc | Parzen density based classifier | |
adaboostc | ADABoost classifier | |
rfishercc | Random Fisher combining classifier | |
treec | Construct binary decision tree classifier | |
dtc | Decision tree classifier, rewritten, also for nominal features | |
statsdtc | Statistical toolbox decision tree | |
randomforestc | Breiman’s random forest classifier | |
naivebc | Naive Bayes classifier | |
statsnbc | Statistical toolbox naive Bayes classifier | |
fdsc | Feature based dissimilarity space classifier |
elements:
datasets
datafiles
cells and doubles
mappings
classifiers
mapping types.
operations:
datasets
datafiles
cells and doubles
mappings
classifiers
stacked
parallel
sequential
dyadic.
user commands:
datasets
representation
classifiers
evaluation
clustering
examples
support routines.
introductory examples:
Introduction
Scatterplots
Datasets
Datafiles
Mappings
Classifiers
Evaluation
Learning curves
Feature curves
Dimension reduction
Combining classifiers
Dissimilarities.
advanced examples.