Methods of identifying patterns in biological systems and uses thereof
First Claim
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1. A computer-implemented method for identifying patterns in data, the method comprising:
- (a) inputting into a classifier a training set having known outcomes, the classifier comprising a decision function having a plurality of weights, each having a weight value, wherein the training set comprises features corresponding to the data and wherein each feature has a corresponding weight;
(b) optimizing the plurality of weights so that classifier error is minimized;
(c) computing ranking criteria using the optimized plurality of weights;
(d) eliminating at least one feature corresponding to the smallest ranking criterion;
(e) repeating steps (a) through (d) for a plurality of iterations until a subset of features of pre-determined size remains; and
(f) inputting into the classifier a live set of data wherein the features within the live set are selected according to the subset of features.
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Abstract
The methods, systems and devices of the present invention comprise use of Support Vector Machines and RFE (Recursive Feature Elimination) for the identification of patterns that are useful for medical diagnosis, prognosis and treatment. SVM-RFE can be used with varied data sets.
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10 Claims
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1. A computer-implemented method for identifying patterns in data, the method comprising:
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(a) inputting into a classifier a training set having known outcomes, the classifier comprising a decision function having a plurality of weights, each having a weight value, wherein the training set comprises features corresponding to the data and wherein each feature has a corresponding weight;
(b) optimizing the plurality of weights so that classifier error is minimized;
(c) computing ranking criteria using the optimized plurality of weights;
(d) eliminating at least one feature corresponding to the smallest ranking criterion;
(e) repeating steps (a) through (d) for a plurality of iterations until a subset of features of pre-determined size remains; and
(f) inputting into the classifier a live set of data wherein the features within the live set are selected according to the subset of features. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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