利用R语言进行SVM..利用R语言进行SVM-REF分析,筛选基因,需要多长时间,我这样会有结果吗,input基因差异表达表格,然后分成了对照组和实验组,直接运行了这个svmREF代码,然后一直回报一个参数,一直回报,不知道
换r的版本，看它报错对应什么版本，你安装那个版本的r就是了
cl <- makeMPIcluster(mpi.universe.size()) clusterExport(cl, list("input","svmRFE","getWeights","svm")) results <-parLapply(cl,folds, svmRFE.wrap, input, k=10, halve.above=100) top.features = WriteFeatures(results, input, save=F) clusterExport(cl, list("top.features","results", ...
SVM-DO: identification of tumor-discriminating mRNA signatures via support vector machines supported by Disease Ontology Our algorithm is available as an R package with a graphical user interface in Bioconductor (https://doi.org/10.18129/B9.bioc.SVMDO) and GitHub (https... ME Zer,P Zbek Saric...
SVM works by finding an optimal hyperplane in a high-dimensional feature space to separate different classes of data points. The margin, which is the distance between the hyperplane and the nearest data points of each class (called support vectors), is found by minimizing the norm of the ...
employed machine learning classifiers, including SVM, Logistic Regression, and XGBoost, as well as deep learning models, such as convolutional neural networks (CNN) and long short-term memory (LSTM) for AFib detection [30]. Out of all models, LSTM obtained the highest accuracy on the MIT-BIH...
refhttps://blog.paperspace.com/faster-r-cnn-explained-object-detection/progressRCNN: Two Stage selective searchCV wrappingpretrained CNN -> SVM classifySVMFast-RCNN: One Stage RoI-PoolingSingle-stage: single CNN pass -> single feature map Why Fast: share feature, reduce computation ...
rxOneClassSvm單一類別支援向量機器。 rxNeuralNet二進位、多類別及迴歸類神經網路。 rxFastLinear適用於線性二進位分類與迴歸的推測雙座標堆疊最佳化。 rxEnsemble將一些各種種類的模型定型,以取得與從單一模型取得的效能相比更佳的預測效能。 2-轉換函式 3-評分與定型函式 ...
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