Huaping Guo

Learn More
In recent years, imbalanced learning problem has attracted more and more attentions from both academia and industry, and the problem is concerned with the performance of learning algorithms in the presence of data with severe class distribution skews. In this paper, we apply the well-known statistical model logistic discrimination to this problem and(More)
Class-imbalance is quite common in real world. For the imbalanced class distribution, traditional state-of-the-art classifiers do not work well on imbalanced data sets. In this paper, we apply logistic regression model to class-imbalance problem, and propose a novel algorithm called CILR (Class Imbalance oriented Logistic Regression) to tackle imbalanced(More)
Poor visibiLity of the hydrauLic drive system, usually to bring some troubleshooting difficult. In this paper, parameter measurement based fault diagnosis method, through quantitative analysis of system parameters and logical analysis, to achieve the accurate diagnosis of the hydrauLic system failure, fault diagnosis with scientific accuracy and rapidity.(More)
This paper proposes a forest pruning method called F-Pruning to improve the performance of ensembles based on decision trees. Instead of trimming each decision tree separately or/and selecting an optimal or sub-optimal subset of base classifiers to form an ensemble, F-Pruning takes a fixed number of trimmed or untrimmed decision trees as a forest (ensemble)(More)
  • 1