Classification algorithm optimization is described. In an example, a classification algorithm is optimized by calculating an evaluation sequence for a set of weighted feature functions that orders the feature functions in accordance with a measure of influence on the classification algorithm. Classification...
(EM) algorithm with a maximum likelihood criterion. Later, from the root model using the maximum a posteriori (MAP) criterion, one GMM per class is constructed. For the training and test data, average log-likelihoods of n-grams using manual orthographic transcriptions are also used in addition...
These issues inspire the authors to investigate and improve the nature inspired optimization algorithm about ACO in this paper. During the previous years, by integrating the complementary strengths of filter and wrapper approaches well, some hybrid methods have been developed to select the significant ...
3.1.2 Constrained methods 然而rehearsal的方法可能会导致过拟合,且性能可能也受到联合训练的限制,constrained optimization 是一种可供选择的解决方案,为向后/向前传输连下了更多的余地。 GEM:GEM在任务增量设置下的关键思想是只约束新的任务更新,而不干扰以前的任务。 实现:通过一阶泰勒级数近似将估计的梯度方向投射...
In addition, the Harris hawks optimization (HHO)-based DBN model is derived as a classifier to allocate appropriate class labels. The design of the HHO algorithm to tune the hyperparameters of the DBN model assists in boosting the classification performance. To examine the superiority of the ...
* Exploring the Algorithm-Dependent Generalization of AUPRC Optimization with List Stability* 链接: arxiv.org/abs/2209.1326* 作者: Peisong Wen,Qianqian Xu,Zhiyong Yang,Yuan He,Qingming Huang* 摘要: Precision-Recall曲线(AUPRC)下区域的随机优化是机器学习的关键问题。尽管已经对各种算法进行了广泛研究以...
Multi-class classification classifies more than two classes in which each instance of a class is mutually exclusive with other classes [1]. Ideally, in the design of the feature-based classification algorithm, we should only choose a small set of high-quality features to train a classifier. Thi...
Ant Colony Optimization–Rain Optimization Algorithm Based on Hybrid Deep Learning for Diagnosis of Lung Involvement in Coronavirus Patients With today's rapid increase in population, automatic diagnosis of disease has emerged as a critical subject in the field of medicine. An automatic disease ... ...
multiple optimization objectives (e.g., inter-cluster separation, tightness, etc.) can be considered simultaneously, resulting in better outcomes in clustering problems. In addition, this hybrid approach retains the advantages of the NSGA2 and FCM methods, allowing the algorithm to be more robust ...
Data preprocessing can improve the FDD performance of multiclass classification-based method. Han et al. introduced PCA to preprocess data for the SVM-based chiller FDD method [68]. Yan et al. introduced an auto-regressive model with exogenous variables algorithm to construct a high dimensional pa...