METHOD AND SYSTEM FOR INFORMATION PREDICTION USING TREE-BASED ENSEMBLE CLASSIFIER

摘要

Disclosed are a system for information prediction using a tree-based ensemble classifier including a data processing module, a learning module, a prediction module, and a database, and a method for the information prediction using the tree-based ensemble classifier by using the system. The method for the information prediction using the tree-based ensemble classifier includes: a data collection step of collecting data for learning; a bootstrap sampling step of bootstrap-sampling the data to classify the data into training data and non-sampled verification data; a kernel fisher discriminant analysis (KFDA) application step of applying a KFDA to the training data; an optimal kernel parameter extraction step of performing verification using the non-sampled verification data and extracting an optimal kernel parameter; a decision tree generation step of generating a decision tree according to the optimal kernel parameter; an ensemble classifier generation step of merging at least two decision trees using a fusion rule to generate a tree-based ensemble classifier; and a step of predicting a class label of new data using the tree-based ensemble classifier with the new data as input data.