Instead of using a single unified GNN model to learn representations for all of the nodes in a large graph, it is better to use ensemble learning methods (37) to improve classification performance.

09/16/2024 Get Code Download Logistic regression is a technique for binary classification -- predicting one of two discrete values. For example, you might want to predict the sex of a person (male = 0 ...

Binary Classification: Classifies text as factual or hallucinated. Bag of Words (BoW): Transforms text into a numerical representation for model training. Custom Logistic Regression: Logistic ...

You can also use the ML.ROC_CURVE function to evaluate logistic regression models; it generates multiple rows with metrics for different threshold values for the model.

Research team led by Chuliang Weng introduces D2-GCN, a groundbreaking disentangled graph convolutional network that dynamically adjusts feature channels for enhanced node representation ...

This paper presents a gender classification model based on face features using logistic regression and K-Nearest Neighbors (KNN) classifier. The dataset contained long hair, forehead breadth, nose ...

This paper employs logistic regression to categorise pumpkin seeds into Urgup_Sivrisi and Cercevelik based on a sample morphological database of 2500 pumpkin seeds from Urgup and Karacaoren, Turkey.