A method and device for presenting a prediction model, and a method and device for adjusting a prediction model. The method for presenting a prediction model includes: obtaining at least one prediction result of a prediction model for at least one prediction sample; obtaining at least one decision-making tree training sample for training a decision-making tree model according to the at least one prediction sample and the at least one prediction result, the decision-making tree model being used for fitting the prediction model; training the decision-making tree model by using at least one decision-making tree training sample; and visually presenting the trained decision-making tree model. By means of the method, a prediction model hard to understand can be approximated to a decision-making tree model, and the approximated decision-making tree model is presented, so that a user better understands the prediction model according to the presented decision-making tree model.

A merchant evaluation method includes: acquiring multi-dimensional evaluation index data of a merchant to be evaluated; for the multi-dimensional evaluation index data, obtaining, by calculation based on standard normal distribution, a health portrait of the merchant to be evaluated, and obtaining, by calculation based on a geometric mean, a health score of the merchant to be evaluated, wherein the health portrait is data representing at least one evaluation result of the merchant to be evaluated; and outputting the health portrait and the health score of the merchant to be evaluated.

A method and apparatus for training an information adjustment model of a charging station, an electronic device, and a storage medium are provided. An implementation comprises: acquiring a battery charging request, and determining environment state information corresponding to each charging station in a charging station set; determining, through an initial policy network, target operational information of each charging station in the charging station set for the battery charging request, according to the environment state information; determining, through an initial value network, a cumulative reward expectation corresponding to the battery charging request according to the environment state information and the target operational information; training the initial policy network and the initial value network by using a deep deterministic policy gradient algorithm; and determining the trained policy network as an information adjustment model corresponding to each charging station.

A system for process shaping in a retail store environment comprises a video generation and processing component, a data source integration and aggregation component for aggregating and integrate information received from various sources, a process sensing component for generating one or more continuous processes, a process aggregator and weighing component for aggregating the one or more continuous processes into a merged weighted process, a proof of problem and value component for determining one or more process variations, a ripple effect analyser for sending one or more nudging messages to the retail store environment, and a gamified feedback algorithm component for communicating a nudging action corresponding to a nudging message, to one or more entities in the retail store environment.

Systems and methods related to the seamless integration of Content Management Interoperability Services (CMIS) client systems with native data models of repositories that may be utilized with such client systems are disclosed. In particular, certain embodiment of systems and methods for the integration of CMIS compliant client systems with CMIS compliant ECM systems by conforming CMIS secondary types utilized by CMIS clients to the native ECM artifacts utilized by the ECM system are disclosed.

A device may receive data that is related to historical reports associated with an organization, historical audits of the historical reports, and individuals associated with the historical reports. The device may determine a multi-entity profile for the data. The multi-entity profile may include a set of groupings of the data by a set of attributes included in the data. The device may determine, using the multi-entity profile, a set of supervised model features for the historical reports. The device may determine, using the multi-entity profile, a set of unsupervised model features for the historical reports independent of the historical audits. The device may determine, utilizing a model, a score for a report. The device may perform one or more actions.

Disclosed herein are system, method, and computer program product embodiments for providing an auto-mapping recommendation between a source asset and a target asset in an integration flow design tool. Because the number of fields passed from a source asset to a target asset may be multitudinous, by auto-recommending mappings between fields provided by the source asset to the target asset, an integration flow design tool may save time developers a significant amount of time and optimize the integration flow design process.

Disclosed herein is a system and method to any two or more MLMs to be merged into a multiline MLM system despite having different commission structures. Each member of the original MLMs is able to maintain their existing downlines without any changes. Further the existing MLM members have full access to the multi-line MLM commission structure, for example, a member of a binary MLM may now add a 3rd, 4th, 5th, etc. line if they choose. The multiline commission plan will be different than the commission plans from any of the original MLMs but this change should not affect the income of a large portion of users, and users that are affected by the changeover can be compensated or made whole on an individual level. In addition to this multiline commission plan, the commission structure of the original MLMs has been broken into several separate ‘types’ which together form a MLM system. These ‘types’ include the income received from downline commission based on position and the income received based on enrolling a member in the MLM, also known as sponsorship. Members with a serious decrease in earnings due to the merger will be awarded points or credits that they can then use to supplement their income going forward. Lines that earn more within a month than the payment cap for that line may draw from the user’s cache of points in order to for the user to receive more in income from a line than the payment cap would normally allow. This way large discrepancies that are due to a member historically having only a few high paying lines can be alleviated and gives these users time to build additional lines without penalty.

Disclosed herein is a system and method to any two or more MLMs to be merged into a multiline MLM system despite having different commission structures. Each member of the original MLMs is able to maintain their existing downlines without any changes. Further the existing MLM members have full access to the multi-line MLM commission structure, for example, a member of a binary MLM may now add a 3rd, 4th, 5th, etc. line if they choose. The multiline commission plan will be different than the commission plans from any of the original MLMs but this change should not affect the income of a large portion of users, and users that are affected by the changeover can be compensated or made whole on an individual level. In addition to this multiline commission plan, the commission structure of the original MLMs has been broken into several separate ‘types’ which together form a MLM system. These ‘types’ include the income received from downline commission based on position and the income received based on enrolling a member in the MLM, also known as sponsorship. Members with a serious decrease in earnings due to the merger will be awarded points or credits that they can then use to supplement their income going forward. Lines that earn more within a month than the payment cap for that line may draw from the user’s cache of points in order to for the user to receive more in income from a line than the payment cap would normally allow. This way large discrepancies that are due to a member historically having only a few high paying lines can be alleviated and gives these users time to build additional lines without penalty.

Systems, methods, and apparatuses for implementing user customizable risk management tools with statistical modeling and a recommendation engine within a computing environment are provided. A system may include, for example, means for evaluating the performance of a user rule for fraud prevention, in which the system receives a plurality of purchase transactions for the user; analyzes each purchase transaction received to generate a fraud likelihood score; receives the rule that specifies conditions when the system is to accept or reject transactions regardless of the fraud likelihood score generated by the system; transmits a historical analysis to the user based on the received rule; receives an input from the user to activate the rule; monitors performance of the rule; and transmits a recommendation to the user to retain or cancel the activated rule based on the monitored performance. Other related embodiments are disclosed.