Man pages for yilinwu123/precision1
PaiREd miCrorna sImulation on Study desIgn for mOlecular classificatioN
| amplify.handling.effect | Handling effect amplification |
| blocking.design | Blocking Design |
| calc.confounding.level | Level of confounding calculation |
| clanc.intcv | Classification to Nearest Centroids Classifier |
| clanc.predict | Prediction with Classification to Nearest Centroids... |
| confounding.design | Confounding Design |
| create.storage | Create Storage for Output |
| dlda.intcv | Diagonal Linear Discriminant Classifier |
| dlda.predict | Prediction with Diagonal Linear Discriminant classifier |
| estimate.biological.effect | Estimated Sample Effects |
| estimate.handling.effect | Estimated handling effects |
| extract.precision.error | Extracting errors from PRECISION (both non-FLEX and FLEX)... |
| knn.intcv | K-Nearest Neighbors Classifier |
| knn.predict | Prediction with K-Nearest Neighbors classifier |
| lasso.intcv | Least absolute shrinkage and selection operator through... |
| lasso.predict | Prediction with least absolute shrinkage and selection... |
| limma.pbset | Differential expression analysis of probe-set data |
| med.norm | Median normalization |
| med.sum.pbset | Probe-set median summarization |
| nuhdata.pl | The nonuniformly-handled probe-level dataset, 10 probes for... |
| pam.intcv | Nearest shrunken centroid through internal cross validation |
| pam.predict | Prediction with nearest shrunken centroid classifier |
| per.unipbset.truncate | Probe-level data truncation to a fixed number of probes per... |
| plot.precision | Plot misclassification error rates from PRECISION (both... |
| plot.precision.multiclass | plot.precision.multiclass |
| precision.simulate | Classification analysis of simulation study |
| precision.simulate.class | precision simulation with classification |
| precision.simulate.multiclass | precision simulation with multi-classification |
| quant.norm | Quantile normalization |
| ranfor.intcv | Random Forest Classifier |
| ranfor.predict | Prediction with random forest classifier |
| reduce.signal | Biological signal reduction |
| rehybridize | Virtual rehybridization with an array-to-sample assignment |
| stratification.design | Stratification Design |
| svm.intcv | Support Vector Machine Classifier |
| svm.predict | Prediction with support vector machine classifier |
| switch.classifier.funcs | Switch classfication functions |
| switch.classifier.funcs.class | Switch classfication functions |
| switch.norm.funcs | Switch Normalization Functions |
| switch.norm.funcs.flex | Switch normalization funcsions in a flexible way |
| tabulate.ext.err.func | Tabulate.ext.err.func |
| uhdata.pl | The uniformly-handled probe-level dataset, 10 probes for each... |
| uni.handled.simulate | Classification analysis of uniformly-handled data |
| vs.norm | Variance stabilizing normalization |
| xgboost.intcv | XGBoost Classifier |
