Method and system for clustering optimization and applications

A computer-assisted method for evaluating a cluster assignment for an observation, comprising the activities of:

• for each of a plurality of observations, obtaining a data set containing no more than one proxy value for each of a plurality of variables, each variable having a plurality of possible values, the data set also containing a cluster assignment for the observation;
• for each observation from the plurality of observations, estimating a purposeful probability that a particular possible value from the plurality of possible values for a particular variable will be purposefully provided by observations assigned to a particular cluster from a plurality of clusters;
• and
• automatically assigning a human respondent associated with a determined observation to a second cluster of the plurality of clusters responsive to a determination that a value of a variable provided by the human respondent causes the human respondent to be classified as an outlier of a first cluster of the plurality of clusters based upon at least one purposeful probability, one or more of the plurality of clusters usable to manage a business tactic.

A computer-readable medium containing instructions for activities comprising:

• for each of a plurality of observations, obtaining a data set containing no more than one proxy value for each of a plurality of variables, each variable having a plurality of possible values, the data set also containing a cluster assignment for the observation, the cluster assignment identifying one cluster from a plurality of clusters;
• for each observation from the plurality of observations, calculating a percent of proxy values for the plurality of variables that equals a mode of that observation's corresponding cluster's proxy values for the corresponding variables;
• and
• automatically assigning a determined observation, of the plurality of observations, to a second cluster of the plurality of clusters responsive to a determination that a value of a variable causes the determined observation to be classified as between a first cluster of the plurality of clusters and the second cluster based upon an output of the percent for the observation, one or more of the plurality of clusters usable to make a medical diagnosis.

An apparatus for evaluating a cluster assignment for an observation, comprising:

• for each of a plurality of observations, means for obtaining a data set containing no more than one proxy value for each of a plurality of variables, each variable having a plurality of possible values, the data set also containing a cluster assignment for the observation, the cluster assignment identifying one cluster from a plurality of clusters;
• for each observation from the plurality of observations, means for calculating a percent of proxy values for the plurality of variables that equals a mode of that observation's corresponding cluster's proxy values for the corresponding variables;
• and
• a processor configured to automatically assign a determined observation, of the plurality of observations, to a cluster responsive to a determination that a fraction of values of variables associated with the determined observation correspond to values typical of the cluster based upon an output of the percent for the determined observation, one or more of the plurality of clusters usable to manage a financial strategy.

A computer-readable medium containing instructions for activities comprising:

• for each of a plurality of observations, obtaining a data set containing no more than one proxy value for each of a plurality of variables, each variable having a plurality of possible values, the data set also containing a cluster assignment for the observation;
• for each observation from the plurality of observations, estimating a purposeful probability that a particular possible value from the plurality of possible values for a particular variable will be purposefully provided by observations assigned to a particular cluster from a plurality of clusters;
• and
• automatically assigning a determined observation of the plurality of observations, to a second cluster of the plurality of clusters responsive to a determination that a fraction of a values of variables associated with the determined observation causes the determined observation to be classified as an outlier of a first cluster of the plurality of clusters based upon an output of at least one purposeful probability, one or more of the plurality of clusters usable to manage a pharmaceutical drug development process.

An apparatus for evaluating a cluster assignment for an observation, comprising:

• for each of a plurality of observations, means for obtaining a data set containing no more than one proxy value for each of a plurality of variables, each variable having a plurality of possible values, the data set also containing a cluster assignment for the observation;
• for each observation from the plurality of observations, means for estimating a purposeful probability that a particular possible value from the plurality of possible values for a particular variable will be purposefully provided by observations assigned to a particular cluster from a plurality of clusters;
• and
• a processor configured to automatically assign a determined observation to a second cluster of the plurality of clusters responsive to a determination that a fraction of a values of variables associated with the determined observation causes the determined observation to be classified as between a first cluster of the plurality of clusters and the second cluster based upon at least one purposeful probability, one or more of the plurality of clusters usable to make an economic decision.