15. A computer system updates at least one prediction model for use by at least one interactive server, wherein each interactive server performs a plurality of actions in the context of a plurality of input attribute values of an input dataset and wherein the actions are selected based on each prediction model, the computer system comprising: a processor; and a memory coupled to the processor, the memory stores a plurality of code modules which when executed by the processor cause the processor to: (a) automatically and continually obtaining contextual data from the interactive server as it performs the plurality of actions, wherein the contextual data indicates at least which action was performed, which input attribute values are present for each action that was performed, and which outcome is achieved for each action was performed; (b) automatically and continually updating a learning model based on all of the obtained contextual data, wherein the learning model predicts a probability of each of a plurality of specific outcomes occurring for each of a plurality of specific actions being performed by the interactive server when specific combinations of one or more input attribute values are present, wherein the updating of the learning model is based on counts of each attribute value as it is present along with each of the other attribute values; (c) generating an updated prediction model, wherein generating comprises, determining a correlation between one or more values of input attributes and a target of prediction, comparing the correlation with a threshold, eliminating each value of input attributes from the input dataset if the value of input attribute falls to satisfy the threshold, and in response to eliminating, generating the updated prediction model based on the input dataset; (d), generating a prediction of a probability of an outcome using the updated prediction model; (e) selecting an action of the plurality of actions based on the prediction; and (f) performing the action, wherein operations (b) and (c) are performed each time a condition is met, the condition being selected from a group consisting of (i) a predetermined level of contextual data has been obtained, (ii) a predetermined number of actions have been performed,(iii) a predetermine time period has expired, and (iv) a number of new input attributes from the collected contextual data has reached a predetermined percentage of a total number input attributes or a predetermined minimum number of new intuit attributes has been reached.
15. A computer system updates at least one prediction model for use by at least one interactive server, wherein each interactive server performs a plurality of actions in the context of a plurality of input attribute values of an input dataset and wherein the actions are selected based on each prediction model, the computer system comprising: a processor; and a memory coupled to the processor, the memory stores a plurality of code modules which when executed by the processor cause the processor to: (a) automatically and continually obtaining contextual data from the interactive server as it performs the plurality of actions, wherein the contextual data indicates at least which action was performed, which input attribute values are present for each action that was performed, and which outcome is achieved for each action was performed; (b) automatically and continually updating a learning model based on all of the obtained contextual data, wherein the learning model predicts a probability of each of a plurality of specific outcomes occurring for each of a plurality of specific actions being performed by the interactive server when specific combinations of one or more input attribute values are present, wherein the updating of the learning model is based on counts of each attribute value as it is present along with each of the other attribute values; (c) generating an updated prediction model, wherein generating comprises, determining a correlation between one or more values of input attributes and a target of prediction, comparing the correlation with a threshold, eliminating each value of input attributes from the input dataset if the value of input attribute falls to satisfy the threshold, and in response to eliminating, generating the updated prediction model based on the input dataset; (d), generating a prediction of a probability of an outcome using the updated prediction model; (e) selecting an action of the plurality of actions based on the prediction; and (f) performing the action, wherein operations (b) and (c) are performed each time a condition is met, the condition being selected from a group consisting of (i) a predetermined level of contextual data has been obtained, (ii) a predetermined number of actions have been performed,(iii) a predetermine time period has expired, and (iv) a number of new input attributes from the collected contextual data has reached a predetermined percentage of a total number input attributes or a predetermined minimum number of new intuit attributes has been reached. 17. A computer system as recited in claim 15 , wherein operations (a) through (c) are performed unsupervised without human intervention.