Abstract: A configuration system may generate synthetic datasets based on machine learning, and may provide the synthetic datasets in order to configure, train, test, and/or otherwise modify operation of network equipment and/or other devices. The configuration system may receive a sampling of data used by the particular network equipment, and may determine parameters that define values for the variables represented in the sampling. The configuration system may generate different datasets based on the parameters, and may determine an accuracy of each dataset to the sampling based on the values of each dataset conforming by different amounts to the parameters that define the values for the variables represented in the sampling by different amounts. The configuration system may modify the network equipment operation using the values from a particular dataset in response to determining that the accuracy of the particular dataset is greatest to the sampling.

Abstract: A configuration system may generate synthetic datasets based on machine learning, and may provide the synthetic datasets in order to configure, train, test, and/or otherwise modify operation of network equipment and/or other devices. The configuration system may receive a sampling of data used by the particular network equipment, and may determine parameters that define values for the variables represented in the sampling. The configuration system may generate different datasets based on the parameters, and may determine an accuracy of each dataset to the sampling based on the values of each dataset conforming by different amounts to the parameters that define the values for the variables represented in the sampling by different amounts. The configuration system may modify the network equipment operation using the values from a particular dataset in response to determining that the accuracy of the particular dataset is greatest to the sampling.

Abstract: Techniques for determining anomalous user behavior in connection with an online application are disclosed. In one embodiment, a method is disclosed comprising obtaining user behavior data in connection with a user of an application, generating feature data using the obtained user behavior data, obtaining one or more user behavior anomaly predictions from one or more anomaly prediction models trained to output a user behavior anomaly prediction in response to the feature data. Each user behavior anomaly prediction indicates a probability that the user behavior is anomalous. A user behavior anomaly determination is made using the user behavior anomaly prediction(s).

Abstract: A configuration system may generate synthetic datasets based on machine learning, and may provide the synthetic datasets in order to configure, train, test, and/or otherwise modify operation of network equipment and/or other devices. The configuration system may receive a sampling of data used by the particular network equipment, and may determine parameters that define values for the variables represented in the sampling. The configuration system may generate different datasets based on the parameters, and may determine an accuracy of each dataset to the sampling based on the values of each dataset conforming by different amounts to the parameters that define the values for the variables represented in the sampling by different amounts. The configuration system may modify the network equipment operation using the values from a particular dataset in response to determining that the accuracy of the particular dataset is greatest to the sampling.

Abstract: A configuration system may generate synthetic datasets based on machine learning, and may provide the synthetic datasets in order to configure, train, test, and/or otherwise modify operation of network equipment and/or other devices. The configuration system may receive a sampling of data used by the particular network equipment, and may determine parameters that define values for the variables represented in the sampling. The configuration system may generate different datasets based on the parameters, and may determine an accuracy of each dataset to the sampling based on the values of each dataset conforming by different amounts to the parameters that define the values for the variables represented in the sampling by different amounts. The configuration system may modify the network equipment operation using the values from a particular dataset in response to determining that the accuracy of the particular dataset is greatest to the sampling.