Anomaly detectors help spot unusual data. Traditional detectors struggle with changing data, so human feedback can help. The new method, ISPForest, combines human input with tree-based detectors to adjust anomaly scores and structure. By updating the model dynamically, the accuracy of anomaly detection improves. Experiments show that human feedback enhances the performance of anomaly detectors on various datasets.