A deep learning binary classification model to predict Customer Churn in R. This project aimed to develop a predictive model to identify potential customer churn in a bank using deep learning ...

Methods: This was an image-based retrospective study using multi-task learning for binary classification. A VGG-16 model was trained on 16,543 non-standardized images. Image data was distributed in ...

Moreover, this research conducts the anomaly classification of IDS based on the deep neural network (DNN) as the Deep Learning (DL) platform and Binary Algorithms (BA) in terms of Binary Bat Algorithm ...

Security remains one of the biggest challenges in the IoT field. This is why several machine learning and deep learning techniques are used to set up models capable of monitoring network traffic and ...

There are many machine learning techniques for binary classification. One of the most powerful techniques is to use the LightGBM (lightweight gradient boosting machine) system. LightGBM is a ...

Nakrani et al. (2020) and Youssef et al. (2020) implemented deep learning models (different types of CNNs) to classify the data. Madhubala et al. (2021) extended the classification to more than two ...