This paper presents an efficient prediction model for a good learning environment using Random Forest (RF) classifier. It consists of a series of modules;�...

Abstract: This paper presents an efficient prediction model for a good learning environment using Random Forest (RF) classifier. It consists of a series of�...

The goal is to establish the relationships between temperature rise and spindle displacement by using LSTM-SVM, which takes the temperature changes at�...

In this paper, we have compared the classification results of two models i.e. Random Forest and the J48 for classifying twenty versatile datasets. We took 20�...

Two-layer ensemble prediction framework has been proposed to predict students' performance based on learning behavior and domain knowledge.

Jan 4, 2024 � Ensemble learning combines multiple machine learning models to produce superior predictive performance compared to a single model. This section�...

Sep 24, 2022 � Ensemble-based machine learning approaches have shown to give better predictive performance than individual models (Rokach, 2010) and have�...

6 days ago � Ensemble forecasting is a modeling approach that combines data sources, models of different types, with alternative assumptions, using distinct pattern�...

Nov 24, 2023 � Ensemble learning is a machine learning technique that improves the performance of machine learning models by combining predictions from multiple models.

In general, student's prior performances are used to train different machine learning models to predict future test or exam performance, similarly to PFA.