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This function implements the AUCRF algorithm for identifying the variables (metabolites) most relevant for the classification task
● Data Source:
CranContrib
● Keywords:
● Alias: aucMCV
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forestPerformance
(Package: RFmarkerDetector) :
Characterizing the performance of a Random Forest model
This function provides the accuracy and the recall of a Random Forest model
● Data Source:
CranContrib
● Keywords:
● Alias: forestPerformance
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This function provides a 'population' estimate of the average OOB error computed for different mtry values, starting from a sample of N models. These values will be used to compute the mtry associated to the minimum averaged OOB error, that is the optimal parameter we are looking for.
● Data Source:
CranContrib
● Keywords:
● Alias: optimizeMTRY
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PCA Loadings plot
● Data Source:
CranContrib
● Keywords:
● Alias: plot.pca.loadings
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A constructor function for the S3 class mccv; the mccv class encapsulates information such as predictions and abels needed to plot roc curve(s) for a cross-validated random forest model
● Data Source:
CranContrib
● Keywords:
● Alias: mccv
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autoscale
(Package: RFmarkerDetector) :
Unit variance scaling method performed on the columns of the data (i.e. metabolite concentrations measured by 1H NMR
The function provides a data pretreatment approach called Autoscaling (also known as unit variance scaling). The data for each variable (metabolite) is mean centered and then divided by the standard deviation of the variable. This way each variable will have zero mean and unit standard deviation.
● Data Source:
CranContrib
● Keywords:
● Alias: autoscale
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rfMCCV
(Package: RFmarkerDetector) :
Monte Carlo cross-validation of Random Forest models
This function allows to perform a Monte Carlo cross-validation of a Random Forest
● Data Source:
CranContrib
● Keywords:
● Alias: rfMCCV
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paretoscale
(Package: RFmarkerDetector) :
Pareto scaling method performed on the columns of the data table (i.e. metabolite concentrations measured by 1H NMR
The function provides a data pretreatment approach called Pareto Scaling. Each column of the table is given a mean of zero by substracting the column column mean from each value in the column; then each value in each column is divided by a scaling factor, represented by the square root of the standard deviation of the column values.
● Data Source:
CranContrib
● Keywords:
● Alias: paretoscale
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rfMCCVPerf
(Package: RFmarkerDetector) :
Extracting average accuracy and recall of a list of Random Forest models
This function provides the average accuracy and the recall of a list of Random Forest models
● Data Source:
CranContrib
● Keywords:
● Alias: rfMCCVPerf
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meanCenter
(Package: RFmarkerDetector) :
Mean centering performed on the columns of the data (i.e. metabolite concentrations measured by 1H NMR
The function allows to have each predictor (column) centered on zero. The average value of each predictor is substracted to each value in the column.
● Data Source:
CranContrib
● Keywords:
● Alias: meanCenter
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providing 
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