MATLAB File Help: prtClassKnn |
prtClassKnn K-nearest neighbors classifier CLASSIFIER = prtClassKnn returns a K-nearest neighbors classifier CLASSIFIER = prtClassKnn(PROPERTY1, VALUE1, ...) constructs a prtClassKnn object CLASSIFIER with properties as specified by PROPERTY/VALUE pairs. A prtClassKnn object inherits all properties from the abstract class prtClass. In addition is has the following properties: k - The number of neigbors to be considered distanceFunction - The function to be used to compute the distance from samples to cluster centers. It must be a function handle of the form: @(x1,x2)distFun(x1,x2). Most prtDistance* functions will work. For information on the K-nearest neighbors classifier algorithm, please refer to the following URL: http://en.wikipedia.org/wiki/K-nearest_neighbor_algorithm A prtClassKnn object inherits the TRAIN, RUN, CROSSVALIDATE and KFOLDS methods from prtAction. It also inherits the PLOT method from prtClass. Example: TestDataSet = prtDataGenUnimodal; % Create some test and TrainingDataSet = prtDataGenUnimodal; % training data classifier = prtClassKnn; % Create a classifier classifier = classifier.train(TrainingDataSet); % Train classified = run(classifier, TestDataSet); % Test classifier.plot;
Superclasses | prtClass |
Sealed | false |
Construct on load | false |
prtClassKnn | K-nearest neighbors classifier |
dataSet | The training prtDataSet, only stored if verboseStorage is true. |
dataSetSummary | Structure that summarizes prtDataSet. |
distanceFunction | Function handle to compute distance |
internalDecider | Optional prtDecider object for making decisions |
isCrossValidateValid | True |
isNativeMary | true |
isSupervised | True |
isTrained | Indicates if prtAction object has been trained. |
k | The number of neighbors to consider in the voting |
name | K-Nearest Neighbor |
nameAbbreviation | KNN |
showProgressBar | |
twoClassParadigm | Whether the classifier retures one output (binary) or two outputs (m-ary) when there are only two unique class labels |
userData | User specified data |
verboseStorage | Specifies whether or not to store the training prtDataset. |
crossValidate | Cross validate prtAction using prtDataSet and cross validation keys. | |
get | get the object properties | |
kfolds | Perform K-folds cross-validation of prtAction | |
optimize | Optimize action parameter by exhaustive function maximization. | |
plot | Plot the output confidence of a prtClass object | |
run | Run a prtAction object on a prtDataSet object. | |
set | set the object properties | |
train | Train a prtAction object using training a prtDataSet object. |