divided by the total number of actual positive classes

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Intent recognition understanding evaluates whether the model can accurately identify the needs and intentions of users. Information retrieval evaluates whether the model can quickly retrieve relevant information from the enterprise knowledge base. Information presentation evaluates whether the information provided by the model is accurate, comprehensive and easy to understand. Performance indicators Accuracy The number of correct predictions divided by the total number of predictions reflects the overall prediction accuracy of the model. Precision The number of correctly predicted positive classes divided by the total number of predicted positive classes reflects the accuracy of the model's predictions of positive classes.



Recall The number of correctly predicted iran phone number format positive classes positive classes. The harmonic mean of the score precision and recall is a metric that takes into account both precision and recall. The area under the curve and the receiver operating characteristic curve measure the performance of the model at all classification thresholds. Efficiency indicators Response time The time required for the model to complete a single prediction affects the user experience and system performance. Resource consumption The demand for computing resources such as memory when the model is running.



Throughput The amount of data that the model can process per unit time. Stability and robustness Stability The consistency and reliability of the model over different time or different data sets. Robustness The ability of the model to maintain performance against noise, outliers or small changes in the input data. Security and privacy protection Data protection ensures that the data processed by the model complies with data protection regulations such as. Access control The access control mechanism provided by the model prevents unauthorized access. Whether the privacy leakage risk assessment model may lead to sensitive information leakage.