Feature modification to change machine learning predictions

Abstract

Systems and methods for analyzing operations to determine factors contributing to a malicious classification and providing recommendations to prevent future misclassifications are disclosed herein. A feature modification system receives operation data associated with monitored operations, where each operation is characterized by a set of feature values. A machine learning-based detection model processes the operation data to generate a prediction indicating whether each operation is malicious. Based on a prediction indicating that an operation has been classified as malicious, the system determines the impact of each feature on the prediction as well as the variability of each feature to identify impactful and modifiable features. The system generates an input dataset including entries with modified features and processes the dataset to obtain a new set of predictions. If a modified entry results in a non-malicious classification, the system generates a recommendation indicating the modifications required to avoid future misclassifications.