Finally, we conduct analyses towards aiding the explainability of the ML models.Kousias, KonstantinosUniv OsloRajiullah, MohammadKarlstad UnivCaso, GiuseppeAlay, OzguBrunstrom, AnnaAli, UsmanDe Nardis, LucaNeri, MarcoDi Benedetto, Maria -Gabriella...
Finally, we conduct analyses towards aiding the explainability of the ML models.Previous article in issue Next article in issue Keywords Mobile networks 5G NSA Machine learning Sorry, something went wrong. Please try again and make sure cookies are enabled...
The appendix delivers detailed master models, representing the correctbest suited model, and evaluation schemes of the experiment, which is helpfulif setting up own empirical experiments.doi:10.4236/jsea.2014.711084VogelHeuserBirgitScientific Research Publishingjournal of software engineering & applicationsB. ...
In order to solve the four-class problem with an SVM classification model, we adopted the one-vs-one strategy, hence we trained 6 different two-class models. The test sample will be assigned to the class characterized by the highest probability (lowest aggregation loss of all the six classifi...
Optimize marketing decision-making through a Unified Marketing Platform. The objective is to optimize marketing decision-making through a Unified Marketing Platform (UMP) powered by a robust marketing data lake and robust ML models. Key challenges UMP can address: Fragmented view of customer and marke...
TinyML is a branch of machine learning (ML) that is focused on deploying ML models to low-power, resource-constrained IoT devices. Deploying ML models on IoT devices has several benefits including reduced latency and preserving privacy as all data is processed on device. TinyML gained traction ...
UsingAmazon Simple Storage Service(Amazon S3) as data storage,data lakecustomers can tap into AWS analytics services such as theAWS GlueCatalog,AWS Glue DataBrew, andAthenafor preparing and transforming data, as well as build trend analysis using ML models inAmazon SageMaker. This...
While deploying ML-based attack detection models on such devices, the run-time computation overhead of the ML models must be carefully controlled at a low level, so that the devices are able to run the ML model to detect attacks even when processing high-bandwidth traffic at the same time ...
Performance analysis of regression‐based machine learning models towards intelligent selection of MIMO configurations (ML) technologies are also being used alongside MIMO since they can aid with the selection of the most appropriate MIMO configuration based on antenna, ... Y Beeharry,DR Calchand - ...
By utilizing ML algorithms and data, it is possible to create smart models that can precisely predict customer intent and as such provide quality one-to-one recommendations.At the same time, the continuous growth of available data has led to information overload — when too many choices ...