Synthesis of microarray-based classification

best | Show best hyperparameter settings |

boxplot | Make a boxplot of the classifier evaluation |

classification | General method for classification with various methods |

classification-methods | General method for classification with various methods |

cloutput-class | "cloutput" |

clvarseloutput-class | "clvarseloutput" |

CMA-package | Synthesis of microarray-based classification |

compare | Compare different classifiers |

compare-methods | Compare different classifiers |

compBoostCMA | Componentwise Boosting |

compBoostCMA-methods | Componentwise Boosting |

dldaCMA | Diagonal Discriminant Analysis |

dldaCMA-methods | Diagonal Discriminant Analysis |

ElasticNetCMA | Classfication and variable selection by the ElasticNet |

ElasticNetCMA-methods | Classfication and variable selection by the ElasticNet |

evaloutput-class | "evaloutput" |

evaluation | Evaluation of classifiers |

evaluation-methods | Evaluation of classifiers |

fdaCMA | Fisher's Linear Discriminant Analysis |

fdaCMA-methods | Fisher's Linear Discriminant Analysis |

filter | Filter functions for Gene Selection |

flexdaCMA | Flexible Discriminant Analysis |

flexdaCMA-methods | Flexible Discriminant Analysis |

ftable | Cross-tabulation of predicted and true class labels |

gbmCMA | Tree-based Gradient Boosting |

gbmCMA-methods | Tree-based Gradient Boosting |

GenerateLearningsets | Repeated Divisions into learn- and tets sets |

genesel-class | "genesel" |

GeneSelection | General method for variable selection with various methods |

GeneSelection-methods | General method for variable selection with various methods |

golub | ALL/AML dataset of Golub et al. (1999) |

internals | Internal functions |

join | Combine list elements returned by the method classification |

join-methods | Combine list elements returned by the method classification |

khan | Small blue round cell tumor dataset of Khan et al. (2001) |

knnCMA | Nearest Neighbours |

knnCMA-methods | Nearest Neighbours |

LassoCMA | L1 penalized logistic regression |

LassoCMA-methods | L1 penalized logistic regression |

ldaCMA | Linear Discriminant Analysis |

ldaCMA-methods | Linear Discriminant Analysis |

learningsets-class | "learningsets" |

nnetCMA | Feed-forward Neural Networks |

nnetCMA-methods | Feed-Forward Neural Networks |

obsinfo | Classifiability of observations |

pknnCMA | Probabilistic Nearest Neighbours |

pknnCMA-methods | Probabilistic nearest neighbours |

Planarplot | Visualize Separability of different classes |

Planarplot-methods | Visualize Separability of different classes |

plot,cloutput-method | Probability plot |

plot,genesel-method | Barplot of variable importance |

plot,tuningresult-method | Visualize results of tuning |

plrCMA | L2 penalized logistic regression |

plrCMA-methods | L2 penalized logistic regression |

pls_ldaCMA | Partial Least Squares combined with Linear Discriminant... |

pls_ldaCMA-methods | Partial Least Squares combined with Linear Discriminant... |

pls_lrCMA | Partial Least Squares followed by logistic regression |

pls_lrCMA-methods | Partial Least Squares followed by logistic regression |

pls_rfCMA | Partial Least Squares followed by random forests |

pls_rfCMA-methods | Partial Least Squares followed by random forests |

pnnCMA | Probabilistic Neural Networks |

pnnCMA-methods | Probabilistic Neural Networks |

prediction | General method for predicting classes of new observations |

prediction-methods | General method for predicting class lables of new... |

predoutput-class | "predoutput" |

qdaCMA | Quadratic Discriminant Analysis |

qdaCMA-methods | Quadratic Discriminant Analysis |

rfCMA | Classification based on Random Forests |

rfCMA-methods | Classification based on Random Forests |

roc | Receiver Operator Characteristic |

scdaCMA | Shrunken Centroids Discriminant Analysis |

scdaCMA-methods | Shrunken Centroids Discriminant Analysis |

shrinkldaCMA | Shrinkage linear discriminant analysis |

shrinkldaCMA-methods | Shrinkage linear discriminant analysis |

summary | Summarize classifier evaluation |

svmCMA | Support Vector Machine |

svmCMA-methods | Support Vector Machine |

toplist | Display 'top' variables |

tune | Hyperparameter tuning for classifiers |

tune-methods | Hyperparameter tuning for classifiers |

tuningresult-class | "tuningresult" |

varseloutput-class | "varseloutput" |

weighted_mcr | Tuning / Selection bias correction |

weighted_mcr-methods | General method for tuning / selection bias correction |

wmc | Tuning / Selection bias correction based on matrix of... |

wmc-methods | General method for tuning / selection bias correction based... |

wmcr_result-class | "wmcr.result" |

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