Abstract: A framework provides a detailed explanation regarding specific aspects of a (complex) calculation produced by an application (e.g., an analytical application). An explainability engine receives a request for explanation of the calculation. The explainability engine traverses homogenous data clusters according to the request, in order to produce a final path. The final path is used to select and then populate a template comprising explanation note(s). The outcome (comprising the final path and the template) is processed with a ruleset according to a covariance (COV) function in order to provide a first intermediate outcome. The first intermediate result is then processed with a second input according to a correlation (COR) function to provide a second intermediate outcome. The second intermediate result is processed according to a challenge function to provide a challenged outcome, and feedback (e.g., reward or penalization) to the ruleset. The challenged outcome provides detailed explanation to the user.

Abstract: Explanation of an analytical result, is afforded to a user by a populating a template with the result of searching homogenous clusters. During a preliminary phase, configuration changes are asynchronously fetched from services of an analytic application, and then grouped into homogenous clusters. Then, during a synchronous phase, a request to explain a particular analytical result is received from the application. Based upon content of the explanation request, the clusters are traversed in order to create a final path. A template comprising an explanation note with blanks, is selected from a template store and then populated with data from the final path. The populated template and the final path are stored together as an outcome. The outcome is then processed according to a challenge function, with the resulting challenged outcome communicated back to the application and afforded to provide the user with an explanation of the analytical result.

Abstract: Methods, systems, and computer-readable storage media for receiving historical data, the historical data including variable vectors, each variable vector being assigned to a class, processing the historical data through encoders to provide feature vectors, each feature vector corresponding to a respective variable vector and being assigned to the class of the respective variable vector, generating a set of decision trees based on the feature vectors, each decision tree corresponding to a class in the set of classes, transforming each decision tree into a set of rules to provide sets of rules, each rule in a set of rules defining conditions to assign at least a portion of an electronic document to a respective class in the set of classes, and providing the sets of rules for execution in an enterprise system, the enterprise system classifying electronic documents to classes in the set of classes based on the sets of rules.

Abstract: Methods, systems, and computer-readable storage media for receiving, by a ML application executing within a cloud platform, a first inference request, the first inference request including first inference data, transmitting, by the ML application, the first inference data to the UAT system within the cloud platform, retrieving, by the UAT system, a first ML model in response to the inference request, the first ML model being in an inactive state, providing, by the UAT system, a first inference based on the first inference data using the first ML model, providing a first accuracy evaluation at least partially based on the first inference, and transitioning the first ML model from the inactive state to an active state, the first ML model being used for production in the active state.

Abstract: Methods, systems, and computer-readable storage media for receiving historical data, the historical data including variable vectors, each variable vector being assigned to a class, processing the historical data through encoders to provide feature vectors, each feature vector corresponding to a respective variable vector and being assigned to the class of the respective variable vector, generating a set of decision trees based on the feature vectors, each decision tree corresponding to a class in the set of classes, transforming each decision tree into a set of rules to provide sets of rules, each rule in a set of rules defining conditions to assign at least a portion of an electronic document to a respective class in the set of classes, and providing the sets of rules for execution in an enterprise system, the enterprise system classifying electronic documents to classes in the set of classes based on the sets of rules.

Abstract: Methods, systems, and computer-readable storage media for receiving user input indicating a first data point representative of output of a machine learning (ML) model, calculating a source model value based on the first data point and a second data point, calculating anti-model sub-values based on the first data point and a set of data points, providing an anti-model value based on the source model value and the anti-model sub-values, and determining a reliability of the output of the ML model based on the anti-model value.

Abstract: A device may receive, from a set of elements of a set of network devices, information associated with a set of parameters. The device may determine an event based on the set of parameters. The device may determine a rule set based on the event. The device may determine other events that are associated with the event based on the rule set. The device may determine statuses of the other events based on the information associated with the set of parameters. The device may evaluate a rule, of the rule set, based on the event and the statuses of the other events. The device may determine an action to be performed based on evaluating the rule. The device may cause the action to be performed in association with the element of the set of elements.

Abstract: According to some embodiments, a method and system provides receiving a list of a plurality of conversations, each of the conversations associated with a common set of characteristics and each of the conversations having associated conversation details; presenting at least a portion of the list of the plurality of conversations in a user interface, each of the conversations included in the presented portion of the list being separately represented; receiving a selection of a plurality of the conversations included in the presented portion of the list; and presenting, simultaneously and grouped together in the user interface, conversation details associated with each of the selected plurality of the conversations, separate and apart from the presented portion of the list.

Abstract: According to some embodiments, a method and system provides receiving a list of a plurality of conversations, each of the conversations associated with a common set of characteristics and each of the conversations having associated conversation details; presenting at least a portion of the list of the plurality of conversations in a user interface, each of the conversations included in the presented portion of the list being separately represented; receiving a selection of a plurality of the conversations included in the presented portion of the list; and presenting, simultaneously and grouped together in the user interface, conversation details associated with each of the selected plurality of the conversations, separate and apart from the presented portion of the list.

Abstract: A method of providing user input values for input controls includes receiving, in a graphical user interface wherein input controls are associated with predefined alternative input values, a first input identifying user selection of at least some of the input controls. The method includes receiving a second input identifying user selection of at least one of the predefined alternative input values that is associated with each of the selected input controls. The second input is made using one of the selected input controls. The method includes entering the selected predefined alternative input value in each of the selected input controls. The value may be automatically entered upon receiving the second input. A third input, for example made with a context menu, may be required to enter the value in the selected controls.

Abstract: A method of providing user input values for input controls includes receiving, in a graphical user interface wherein input controls are associated with predefined alternative input values, a first input identifying user selection of at least some of the input controls. The method includes receiving a second input identifying user selection of at least one of the predefined alternative input values that is associated with each of the selected input controls. The second input is made using one of the selected input controls. The method includes entering the selected predefined alternative input value in each of the selected input controls. The value may be automatically entered upon receiving the second input. A third input, for example made with a context menu, may be required to enter the value in the selected controls.