Method for enhancing knowledge discovered from biological data using a learning machine

A method for enhancing knowledge discovered from biological data using a support vector machine comprising the steps of:

• pre-processing a training data set derived from biological data to add meaning to each of a plurality of training data points;
• training the support vector machine using the pre-processed training data set;
• pre-processing a test data set derived from biological data to expand each of a plurality of test data points;
• testing the trained support vector machine using the pre-processed test data set to generate a test output;
• and
• in response to receiving the test output of the trained support vector machine, post-processing the test output to determine if the test output is an optimal solution.

A system for enhancing knowledge discovered from biological data using a support vector machine comprising:

• a storage device for storing a training data set and a test data set;
• a processor for executing a support vector machine;
• the processor further operable for:
• collecting the training data set from the database,
• pre-processing the training data set to add meaning to each of a plurality of training data points,
• training the support vector machine using the pre-processed training data set;
• in response to training the support vector machine, collecting the test data set from the database,
• pre-processing the test data set to expand each of a plurality of test data points,
• testing the trained support vector machine using the pre-processed test data set to generate a test output, and
• in response to receiving the test output of the trained support vector machine, post-processing the test output to determine if the test output is an optimal solution.

A method for diagnosing disease, comprising, using a learning machine comprising,

• a) pre-processing a training data set derived from biological data to expand each of a plurality of training data points;
• training the learning machine using the pre-processed training data set;
• pre-processing a test data set derived from biological data to expand each of a plurality of test data points;
• testing the trained learning machine using the pre-processed test data set to generate a test output;
• and
• in response to receiving the test output of the trained learning machine,
• post-processing the test output to determine if the knowledge discovered from the pre-processed test data set is desirable.