Abstract: Apparatuses, systems, methods, and computer program products are disclosed for data quality detection and compensation for machine learning. A quality analysis module electronically identifies one or more data quality issues in machine learning training data. A corrective action module modifies training data by performing one or more corrective actions in response to one or more data quality issues. A predictive analytics module creates a machine learning model that includes one or more learned functions based on modified training data.

Abstract: Apparatuses, systems, methods, and computer program products are disclosed for drift detection and correction for predictive analytics. A prediction module applies a model to workload data to produce one or more predictive results. Workload data may include one or more records. A model may include one or more learned functions based on training data. A drift detection module detects a drift phenomenon relating to one or more predictive results. A predict-time fix module may modify at least one predictive result in response to a drift phenomenon.