Abstract: This application describes systems and methods for generating machine learning models (MLMs). An exemplary method includes obtaining a sample and user input data characterizing a product or service. A subset of the data is selected from the sample based on sampling the sample according to the user input data. An MLM is trained by applying the data subset as training input to the MLM, thereby providing a trained MLM to emulate a customer selection process unique to the product or service. A user interface (UI) configured to receive other user input data and cause the trained MLM to execute on the other user input data, thereby testing the trained MLM, is presented. A summary of results from the execution of the trained MLM is generated and presented in the UI. The summary of results indicates a contribution to the trained MLM of each of a plurality of features.

Abstract: Aspects of the present disclosure relate to adverse user behavior detection and mitigation. In examples, a user account of a social platform may be trusted or untrusted. If the user account is untrusted, activity of the user account may be buffered so as to not directly affect social metrics of the social platform. For example, if the untrusted user account follows a target user account, the untrusted user account may be added to a separate set of followers or otherwise separated from a set of trusted followers of the target user account. Eventually, each user account in the separate set is evaluated to determine whether the user account has transitioned to a trusted user. If the user account is now trusted, it may be migrated to the set of trusted followers. However, if the user account is untrusted, it may be removed from the separate set, thereby reverting the activity.

Abstract: Techniques for pain surveying and visualization in a bodily region including a 3-dimensional rendering of a bodily region or an anatomical grid for presentation to a subject suffering from pain for collection of pain intensity and pain location information. A device is provided to the patients for display of the rendering of the bodily region or anatomical grid for collection of pain intensity and location information. A pain analysis module may then create an aggregate pain data set for visual data analyses, user reports, or data export focused on one or multiple region(s), as well as the entire body. The pain data sets may include patient data from a single patient or aggregated data from multiple patients.

Abstract: A system and method for providing highly available and/or fault tolerant servers by implementing a lookup table or other data structure that allows a common file handle to be generated and interpreted by any component server of the HA server, thereby preventing stale file handles and removing local file system requirements as to media, implementation, and location.