Abstract: A feature engineering engine is included in an analytics application provided to at least one subscriber from a plurality of subscribers. The feature engineering engine generates a reduced discovery dataset based on an input dataset and stores at least a portion of the reduced discovery dataset in cache memory associated with the analytics application. While displaying at least a portion of the reduced discovery dataset, the feature engineering engine performs one or more entity resolution operations and generates an instantiated set of features. In some embodiments, the instantiated set of features is generated based on a previously generated, reusable feature definition. In some embodiments, using the instantiated set of features, a trained machine learning model is automatically selected from a plurality of models based on a performance metric determined for the instantiated set of features.

Abstract: Systems and methods for reducing network traffic associated with generating event predictions based on cognitive image analysis are disclosed. The system receives a user input indicating a location identifier of a location of interest. The system queries a data store to determine whether an image associated with the location of interest satisfies a data recency criterion. In response to the image failing to satisfy the data recency criterion, the system queries a remote data store to determine whether another, additional image associated with the location of interest satisfies the data recency criterion. In response to the additional image satisfying the data recency criterion, the system extracts one or more image-based attributes of the additional image and determines a distance between objects of the image. The system generates an event prediction based on the image-based attributes, the distance, and location-based attributes using a machine learning model to be displayed.

Abstract: Systems and methods consistent with the present invention manage a credit card having an adjustable credit limit. The system determines whether the credit limit is likely to be reached by possible transactions made by the customer when using the account. The system adjusts the credit limit when it is determined that the credit limit is likely to be reached. The adjusted credit limit is analyzed to determine whether it satisfies predefined credit limit amount criteria associated with the account. The system then revises the adjusted credit limit, as necessary, such that the revised credit limit satisfies the predetermined credit criteria.

Abstract: Systems and methods consistent with the present invention manage a credit card having an adjustable credit limit. The system determines whether the credit limit is likely to be reached by possible transactions made by the customer when using the account. The system adjusts the credit limit when it is determined that the credit limit is likely to be reached. The adjusted credit limit is analyzed to determine whether it satisfies predefined credit limit amount criteria associated with the account. The system then revises the adjusted credit limit, as necessary, such that the revised credit limit satisfies the predetermined credit criteria.