Abstract: A plurality of neural networks or other models can be used in employee selection technologies. A hiring recommendation can be based at least on processing performed by a plurality of neural networks. For example, parallel or series processing by neural networks can be performed. A neural network can be coupled to one or more other neural networks. A binary or other n-ary output can be generated by one or more of the neural networks. In a series arrangement, candidates can be processed sequentially in multiple stages, and those surviving the stages are recommended for hire.

Abstract: An employee can be selected (e.g., employee job performance can be predicted) via a predictive model. Items presented as part of an assessment can be chosen according to which has greatest predictive power. The next item to be presented can be selected based on imputation of inputs to the predictive model for items not yet presented. Expected reduction in estimated output variance can be calculated.