| ad.matrix | An adjacency matrix of a sample graph... |
| calc.diffusionKernelp | Computing the Random Walk Kernel matrix of network |
| classify.aep | Training and predicting using aepSVM (aepSVM) classification... |
| classify.frsvm | Training and predicting using FrSVM |
| classify.hubc | Training and predicting using hub nodes classification... |
| classify.pac | Training and predicting using PAC classification methods |
| classify.stsvm | Training and predicting using stSVM classification methods |
| cv.aep | Cross validation for aepSVM (aepSVM) |
| cv.frsvm | Cross validation for FrSVM |
| cv.hubc | Cross validation for hub nodes classification |
| cv.pac | Cross validation for Pathway Activities Classification(PAC) |
| cv.stsvm | Cross validation for smoothed t-statistic to select... |
| EN2SY | An list for mapping gene entre ids to symbol ids |
| expr | Two expression profile matrixs and their labels |
| getGeneRanking | Get gene ranking based on geneRank algorithm. |
| getGraphRank | Random walk kernel matrix smoothing t-statistic |
| Gs2 | An subgraph of hub nodes |
| netClass-package | An R package for network-Based microarray Classification |
| pGeneRANK | GeneRANK |
| pOfHubs | Computing p value of hubs using the permutation test |
| predictAep | Predicting the test tdata using aep trained model |
| predictFrsvm | Predicting the test data using frsvm trained model |
| predictHubc | Predicting the test data using hubc trained model |
| predictPac | Predicting the test data using pac trained model |
| predictStsvm | Predicting the test data using stsvm trained model |
| probeset2pathway | Generae a mean gene expression of genes of each pathway... |
| probeset2pathwayTrain | Search CROG in training data |
| probeset2pathwayTst | Applied CROG to testing data |
| train.aep | Training the data using aep methods |
| train.frsvm | Training the data using frsvm method |
| train.hubc | Predicting the data using hub nodes classification model |
| train.pac | Training the data using pac methods |
| train.stsvm | Training the data using stsvm methods |
