Incremental clustering classifier and predictor

A method of predicting, comprising the steps of:

• receiving a pre-existing classification structure;
• receiving an instance to be predicted, comprising at least one attribute to be predicted;
• determining a best host for the instance to be predicted;
• optionally placing the instance to be predicted into a location relative to at least one child of the best host within the pre-existing classification structure;
• determining a confidence level for an occurrence of an at least one possible value for the at least one attribute to be predicted;
• and
• returning a prediction profile, comprising at least one possible value for the at least one attribute to predict and the corresponding confidence level for the at least one possible value for the at least one attribute to be predicted.

A method comprising the steps of:

• receiving a data set comprising instances to be classified, wherein each instance to be classified is comprised of at least two attributes and corresponding relevance values;
• building a first classification structure from the data set of instances to be classified;
• determining the prediction accuracy of the first classification structure;
• establishing at least one prediction accuracy acceptability criterion for using a classification structure to predict attribute values;
• building subsequent classification structures, wherein less attributes of the instances to be classified are used for classifying the instances into each subsequent classification structure;
• determining the prediction accuracy of each the subsequent classification structure;
• discarding unacceptable classification structures;
• and
• retaining at least one subsequent classification structure which uses less attributes and yields prediction accuracy results that fall within the at least one prediction accuracy acceptability criterion.

A method comprising the steps of:

• receiving at least one data set comprising at least one instance to be classified;
• receiving a federated group number;
• and
• constructing a federated group number of classification structures comprising
• selecting a subset of the federated group number of classification structures, wherein the subset comprises a classification overlap number;
• and
• classifying a copy of the at least one instance to be classified within each member of the subset of the federated group number of classification structures.

A method of predicting comprising the steps of:

• receiving a group of classification structures;
• receiving an instance with an at least one attribute to predict;
• querying each member of a subset of the group of classification structures to perform a prediction process on the instance;
• and
• returning a coalesced prediction profile.