Abstract: A method and system are provided to calculate a future behavioral data and identify a relative causal impact of external factors affecting the data. Behavioral data and data for one or more external factors are harvested for a first time period. New behavioral data is harvested for a second time period. New data for the second time period is harvested. Based on a second training algorithm, a forecast time series value of a future behavioral data for a third time period that is after the second time period is calculated. A relative causal impact between each external factor and the predicted time series value of the behavioral data, for the third time period, is identified.

Abstract: Techniques for learning from highly-diverse datasets are provided. In one embodiment, the system is provided that comprises a memory that stores computer executable components. The system can comprise a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a neural network component that creates a neural network comprising a router that routes the neural network to a first layer of neurons that comprises a plurality of neurons. The computer executable components can comprise a training component that performs a plurality of successive training iterations on the neural network, a first iteration of the plurality of successive training iterations comprising both training the router to route among the plurality of neurons of the first layer of neurons, and training a first neuron of the plurality of neurons of the first layer of neurons to produce a given output from a given input.

Abstract: A method and system are provided to calculate a future behavioral data and identify a relative causal impact of external factors affecting the data. Behavioral data and data for one or more external factors are harvested for a first time period. New behavioral data is harvested for a second time period. New data for the second time period is harvested. Based on a second training algorithm, a forecast time series value of a future behavioral data for a third time period that is after the second time period is calculated. A relative causal impact between each external factor and the predicted time series value of the behavioral data, for the third time period, is identified.