| PERCEPTRON | |
Perceptron algorithm to train binary linear classifier.
Synopsis:
model = perceptron(data)
model = perceptron(data,options)
model = perceptron(data,options,init_model)
Description:
model = perceptron(data) uses the Perceptron learning rule
to find separating hyperplane from given binary labeled data.
model = perceptron(data,options) specifies stopping condition of
the algorithm in structure options:
.tmax [1x1]... maximal number of iterations.
If tmax==-1 then it only returns index (model.last_update)
of data vector which should be used by the algorithm for updating
the linear rule in the next iteration.
model = perceptron(data,options,init_model) specifies initial model
which must contain:
.W [dim x 1] ... normal vector.
.b [1x1] ... bias of hyperplane.
.t [1x1] (optional) ... iteration number.
Input:
data [struct] Labeled (binary) training data.
.X [dim x num_data] Input vectors.
.y [1 x num_data] Labels (1 or 2).
options [struct]
.tmax [1x1] Maximal number of iterations (default tmax=inf).
If tmax==-1 then it does not perform any iteration but returns only
index of the point which should be used to update linear rule.
init_model [struct] Initial model; must contain items
.W, .b and .t (see above).
Output:
model [struct] Binary linear classifier:
.W [dim x 1] Normal vector of hyperplane.
.b [1x1] Bias of hyperplane.
.exitflag [1x1] 1 ... perceptron has converged.
0 ... number of iterations exceeded tmax.
.t [int] Number of iterations.
.last_update [d x 1] Index of the last point used for update.
Example:
data = genlsdata( 2, 50, 1);
model = perceptron(data)
figure; ppatterns(data); pline(model);
See also
EKOZINEC, MPERCEPTRON, LINCLASS.
About: Statistical Pattern Recognition Toolbox
(C) 1999-2003, Written by Vojtech Franc and Vaclav Hlavac
Czech Technical University Prague
Faculty of Electrical Engineering
Center for Machine Perception
Modifications:
17-sep-2003, VF
16-Feb-2003, VF
20-Jan-2003, VF
7-jan-2002, VF. A new coat.
24. 6.00 V. Hlavac, comments polished.
15-dec-2000, texts, returns bad point