1. A computer-implemented method for classifying and displaying small collections of high-value entities that have missing data, the method comprising: gathering available data about relevant attributes of high-value entities that are to be classified, wherein the relevant attributes include one dependent variable and multiple independent variables for each high-value entity, wherein the dependent variable identifies a particular high-value entity, and wherein the independent variables are values that represent answers to questions asked about the particular high-value entity; classifying the high-value entities by assigning each high-value entity into a category based on properties in common with other members of that category and in contrast with members of other categories; in response to receiving a future high-value entity that has missing data, evaluating a category for the future high-value entity based on properties which the future high-value entity has in common with past or current members of the category and how the future high-value entity aligns with previously classified high-value entities, which category is identified via classifying the future high-value entities with missing data into categories; assigning the future high-value entity to the category identified via the evaluating; wherein the small collections of high-value entities are a set of entities that is too small for statistical methods and neural networks, which require relatively large samples to perform a classification; wherein the high-value entities are objects whose individual worth is substantial enough to justify classification, even if a total number of objects is too small to attain statistical significance or neural network convergence; wherein the classifying identifies which properties define each category in order to (1) select appropriate actions for an entity based on the entity's assigned category, (2) move an entity from one category to another, and (3) affect the properties of an entire category; and wherein the independent variables are one or more of facts and opinions, both objective and subjective, and are quantifiable on one of an interval and a ratio measurement scale, and related independent variables are organized into multiple dimensions that are each weighted separately.