Part V : the Ensemble Prediction System ( Cy 23 R 4 )

Part III : DYNAMICS AND NUMERICAL PROCEDURES ( CY 23 R 4 )

Application of ensemble learning techniques to model the atmospheric concentration of SO2

In view of pollution prediction modeling, the study adopts homogenous (random forest, bagging, and additive regression) and heterogeneous (voting) ensemble classifiers to predict the atmospheric concentration of Sulphur dioxide. For model validation, results were compared against widely known single base classifiers such as support vector machine, multilayer perceptron, linear regression and re...

Ifs Documentation Part V: the Ensemble Prediction System

IFS Documentation Cycle CY25r1 IFS DOCUMENTATION PART V: THE ENSEMBLE PREDICTION SYSTEM

Ensemble-based Top-k Recommender System Considering Incomplete Data

Recommender systems have been widely used in e-commerce applications. They are a subclass of information filtering system, used to either predict whether a user will prefer an item (prediction problem) or identify a set of k items that will be user-interest (Top-k recommendation problem). Demanding sufficient ratings to make robust predictions and suggesting qualified recommendations are two si...