1. A method comprising: collecting a plurality of configurations from a plurality of computing resources, respectively; processing the plurality of configurations to generate one or more rules, wherein the one or more rules are generated by an analyzer; analyzing one or more first configurations out of the plurality of configurations using the one or more rules to produce an analysis result, wherein each of the first configuration(s) defines a configuration of a respective computing resource; training a Bayesian classifier using the analysis result, wherein the training generates one or more weights, and the Bayesian classifier takes as an input the first configurations of the respective computing resources; classifying a second configuration using the trained Bayesian classifier, wherein the classifying uses the weight(s); and modifying the trained Bayesian classifier in response to a modification of the classified second configuration, wherein the trained Bayesian classifier adjusts at least one of the weight(s) based on the modified Bayesian classifier.
1. A method comprising: collecting a plurality of configurations from a plurality of computing resources, respectively; processing the plurality of configurations to generate one or more rules, wherein the one or more rules are generated by an analyzer; analyzing one or more first configurations out of the plurality of configurations using the one or more rules to produce an analysis result, wherein each of the first configuration(s) defines a configuration of a respective computing resource; training a Bayesian classifier using the analysis result, wherein the training generates one or more weights, and the Bayesian classifier takes as an input the first configurations of the respective computing resources; classifying a second configuration using the trained Bayesian classifier, wherein the classifying uses the weight(s); and modifying the trained Bayesian classifier in response to a modification of the classified second configuration, wherein the trained Bayesian classifier adjusts at least one of the weight(s) based on the modified Bayesian classifier. 9. The method of claim 1 , further comprising: evaluating configuration data to determine a relationship amongst the first configuration(s).