EP0690406A2
Expired / Lapsed
EP
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Soft margin classifier
Assignee: AT&T Inc
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Filing: 1995-06-20
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Granted: —
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Expires: 2015-06-20
Abstract
Abstract A soft margin classifier and method are disclosed for processing input data of a training set into classes separated by soft margins adjacent optimal hyperplanes. Slack variables are provided, allowing erroneous or difficult data in the training set to be taken into account in determining the optimal hyperplane. Inseparable data in the training set are separated without removal of data obstructing separation by determining the optimal hyperplane having minimal number of erroneous classifications of the obstructing data. The parameters of the optimal hyperplane generated from the training set determine decision functions or separators for classifying empirical data. <MATH>
Inventors
- 👤 Corinna Cortes
- 👤 Vladimir Vapnik
Bibliographic Details
Application Number
—
Jurisdiction
EP
Data Source
google_patents
Last Synchronized
2026-11-02 10:37
CPC Classifications
G; G06; G06N; G06N20/00; G06N20/10; G06F; G06F18/00; G06F18/20; G06F18/24; G06F18/241; G06F18/2411
Claims Analysis
Total Claims: 10
Claim 1
Independent Claim
90 words
A system for differentiating data vectors to
produce a signal indicating membership status of each data
vector in a class, the system comprising: a processing unit including memory for storing the
data vectors; stored programs including a data vector
processing program; and a processor controlled by the
stored programs and including: means for determining parameters including slack
variables from the data vectors, the parameters
representing a multidimensional surface differentiating
the data vectors with respect to the class; and means for generating the signal from the data
vectors and the parameters.
Claim 2
Dependent Claim
35 words
The system of claim 1 wherein the generating
means evaluates a decision function of the parameters and
each data vector to indicate membership of a respective
data vector in the class to generate the signal.
Claim 3
Dependent Claim
24 words
The system of claim 2 wherein the generating
means generates the signal from a sign function of a value
of the evaluated decision function.
Claim 4
Dependent Claim
24 words
The system of claim 3 wherein the determining
means determines the parameters including a weight vector
and a bias from a plurality of constraints.
Claim 5
Dependent Claim
33 words
The system of claim 4 wherein the generating
means evaluates the decision function from a linear sum of
the bias and a dot product of the weight vector and a
respective data vector.
Claim 6
Dependent Claim
34 words
The system of claim 4 wherein the
determining means determines a minimum non-negative value
of the slack variables for each data vector from the weight vector and the bias
satisfying the plurality of constraints.
Claim 7
Dependent Claim
104 words
A classifier for classifying data vectors to produce a signal
representing membership status of each data vector with respect to a plurality of
classes, the classifier comprising: means for providing the data vectors to be classified; memory for receiving and storing the data vectors and stored programs
including a data vector processing program; and a processor controlled by the data vector processing program and
including: means for determining parameters including slack variables from the
data vectors, the parameters representing a multidimensional surface separating the
data vectors into the plurality of classes; and means for generating the signal from the data vectors and the
parameters.
Claim 8
Dependent Claim
18 words
The classifier of claim 7 wherein the determining means determines
the parameters to represent an optimal multidimensional surface.
Claim 9
Dependent Claim
70 words
The classifier of claim 7 further comprises: means for inputting a class separator value; the processor further includes means for parsing the data vectors to
extract class labels therefrom; the determining means determines the parameters as a decision function
corresponding to the class separator value; and the generating means generates the signal indicating data vectors with
corresponding class labels are members of the class corresponding to the class
separator value.
Claim 10
Dependent Claim
43 words
The classifier of claim 7 wherein the classifier classifies a training set
of pattern vectors as the data vectors and the generating means generates the signal
to indicate the membership of each pattern vector in the training set with respect to
the class.
References Cited (Backward Citations)
US9778593B2
Cited
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