DATASET

Dataset class constructor

     A = DATASET(DATA,LABELS)

Input
DATA	size [M,K] a set of M datavectors (objects) of length K.  a cell array of datasets will be concatenated.
LABELS	size [M,N] array with labels for the M datavectors.  They should be either integers or character strings.  Choose single characters for the fastest implementation.  Numeric labels with value NaN or character labels  with value CHAR(0) are interpreted as missing labels.

Output
A	Dataset

Description

This command is the class constructor for datasets. In addition to the object labels  various other types of information can be stored in the fields of A.  These fields are

DATA	size [M,K] array (doubles) with M K-dimensional feature vectors (objects)
FEATLAB	size [K,F] array with labels for the K features
FEATDOM	size [K] cell array with domain description for the K features
TARGETS	size [M,C] dataset with soft labels or targets
PRIOR	size [C,1] prior probabilities for each of the C classes PRIOR = 0: all classes have equal probability 1/C PRIOR = []: all datavectors are equally probable
COST	size [C,C+1] Classification cost matrix. COST(I,J) are the costs  of classifying an object from class I as class J.  Column C+1 generates an alternative reject class and  may be omitted, yielding a size of [C,C].  An empty cost matrix, COST = [] (default) is interpreted  as COST = ONES(C) - EYE(C) (identical costs of  misclassification).
LABLIST	size [C,N] class labels corresponding to the unique labels found  in LABELS and thereby to the classes in the dataset.  The order of the items in LABLIST corresponds to the  apriori probablities stored in PRIOR. LABLIST should  only be given explicitely if PRIOR is given and if it  is not equal to 0 and not empty.
LABTYPE	String defining the label type,  'crisp' for defining classes by integers or strings  'soft' for defining memberships to classes. In this  case LABELS should be a MxC array with numbers  between 0 and 1.  'targets' for defining regression type target values.  Labels should be a MxN numeric array for  defining N targets per object.
OBJSIZE	number of objects, or vector with its shape. This is  useful if the set of objects can be interpreted as an  image (objects are pixels).
FEATSIZE	number of features, or vector with its shape. This is  useful if the set of features can be interpreted as an  image (features are pixels).
IDENT	[M,1] Cell array, identifier for objects.
NAME	String with dataset name
USER	User definable variable
VERSION	Date and PRTOOLS version at creation

The fields LABLIST, OBJSIZE, FEATSIZE, IDENT and VERSION are preset by PRTOOLS.  The other fields can be set by the user by the below SET commands.  All fields can be read by GET commands. By STRUCT(A) a dataset A can be  converted to a structure. By DOUBLE(A) or +A the data can be retrieved.  HELP DATASETS lists more information.

See also

datasets, mappings,