Abstract: Embodiments herein disclose a method and network apparatus for network performance evaluation using AI-based network cloning. The method includes constructing one or more AI-based network clones of one or more network nodes. The one or more AI-based network clones mimics a data pattern and cell behavior of the one or more network nodes. Further, the method includes receiving a solution predicted by an AI server to mitigate one or more problems associated with one or more services of the one or more network nodes. Further, the method includes evaluating a performance of the one or more AI-based network clones by deploying the solution on the one or more AI-based network clones. Further, the method includes sending the solution to the one or more network nodes for deployment or retraining based on the performance of the one or more AI-based network clones.

Abstract: A system and/or method for automated ML model retraining by an electronic device. The system and/or method may include one or more of: running a first ML model and a second ML model, predicting an accuracy degradation of the first ML model using the second ML model, determining whether the predicted accuracy degradation meets a pre-defined threshold, and/or retraining the first ML model when the predicted accuracy degradation meets the pre-defined threshold.