Compare SVM mode yoga movement classification accuracy with Linear kernel, Polynomial kernel, RBF (Radial Basis Function) kernel, LSTM with accuracy up to 98%. In addition, it also supports adjusting the practitioner's movements according to standard movements. machine-learning computer-vision deep-le...
RBF-SVM kernel-based model for detecting DDoS attacks in SDN integrated vehicular networkGoodness Oluchi Anyanwu a EnvelopeCosmas Ifeanyi Nwakanma b EnvelopeJae Min Lee a EnvelopeDong-Seong Kim a Person EnvelopeAd Hoc Networks
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>>>importdask_ml.model_selectionasdcv>>>fromsklearnimportsvm, datasets>>>iris = datasets.load_iris()>>>parameters = {'kernel': ['linear','rbf'],'C': [1,10]}>>>svc = svm.SVC()>>>clf = dcv.GridSearchCV(svc, parameters)>>>clf.fit(iris.data, iris.target)GridSearchCV(cache_cv...
The rapid growth and adaptation of medical information to identify significant health trends and help with timely preventive care have been recent hallmarks of the modern healthcare data system. Heart disease is the deadliest condition in the developed w
The three kernel functions used are the linear, Radial Basis Function (RBF), and sigmoid kernels. The models were trained and evaluated on five levels of degree in modeling. The degree of the polynomial kernel determines the complexity of the decision boundary, with higher degrees allowing for ...
(X) self.model = self.train_svm(trainvectors=X, labels=y, c='search', kernel='search', gamma='search', degree='search', jobs=4) # self.model = self.train_regression(trainvectors=X, labels=y, c='search', penalty='search', tol='search') logging.info('Finishi...
a关键词:SBR聚合转化率;软测量; RBF;LSSVM;PLS;多模型;短期校正 Key word: SBR polymerization conversion rate; Soft survey; RBF; LSSVM; PLS; Multi-models; Short-term adjustment[translate]
1)通过对丁苯橡胶聚合工艺的分析,选取胶浆温度、环境温度、水平压差和垂直压差为辅助变量,进行相应的数据采集与处理。根据不同软测量模型建模的快速性、对数据样本的敏感性、性能互补以及预测精度等方面的考虑,初选RBF、LS-SVM及PLS方法建立丁苯橡胶聚合转化率预测的单模型,并在以MATLAB为仿真试验平台分析各个模型精度及...
For short-term trafficflow prediction,this paper applies a combination prediction base on RBF-SVM model.At first,it is to use RBF and SVM to get separately two prediction values,then each error can be calculated by each prediction value .Using the two errors to adjust the two weights.At ...