Abstract: There is a need for more effective and efficient predictive data analysis. This need can be addressed by, for example, solutions for performing/executing hybrid input predictive data analysis.

Abstract: Various embodiments of the present invention disclose techniques for implementing an automatic data processing scheme for evaluating robust data sets to optimize procedure efficiency. A method may include determining a weighting-based input data object parameter for a robust data set; determining a variance-based input data object cohort parameter for a subset of the robust data set; generating a predictive variance metric for a data object of the subset based at least in part on the variance-based input data object cohort parameter and a first predictive metric attribute for the data object; generating a predictive weighting metric for the data object based at least in part on the weighting-based input data object parameter and a second predictive metric attribute for the data object; and generating a predictive metric data object for evaluating the robust data set based at least in part on the predictive variance metric and the predictive weighting metric.