Systems and methods for expert-assisted classification are described herein. An example method for evaluating an expert-assisted classifier can include providing a cascade classifier including a plurality of classifier stages; and providing a simulated expert stage between at least two of the classifier stages. The simulated expert stage can be configured to validate or contradict an output of one of the at least two classifier stages. The method can also include classifying each of a plurality of records into one of a plurality of categories using the cascade classifier combined with the simulated expert stage; and determining whether the simulated expert stage improves performance of the cascade classifier.We have developed a novel method of classification using a machine learning classifier that works in tandem with human experts trained to identify each specific class. The expert-assisted cascading classifier approach is a multistage, multiclass cascading classification technique that achieves higher classification accuracy. The novel framework involves domain experts at each stage of classification to further improve the performance of the classification system. The classifier may be used as a decision aid to reduce the effort of domain experts and provides a unique opportunity to include them at each stage.
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