Statistical Analysis - Aster Analytics

• CrossValidation . The CrossValidation function validates a model by assessing how the results of a statistical analysis generalize to an independent data set.
• DenseSVM Functions:
  • DenseSVMTrainer. The DenseSVMTrainer function takes training data and builds a predictive linear or nonlinear model in binary format.
  • DenseSVMPredictor. The DenseSVMPredictor function uses the model to predict the class of each sample in a test data set.
  • DenseSVMModelPrinter. The DenseSVMModelPrinter function displays readable information about the model.
• PCAPlot. The PCAPlot function takes the principal components output by the Principal Component Analysis (PCA) function and input data, changes the basis of the input data to the principal components, and outputs the result.
• RandomSample. The RandomSample function takes a data set and uses a specified sampling method to output one or more random samples. Each sample has exactly the number of rows specified. The RandomSample function is useful for generating test sets, training sets, and initial centers for clustering algorithms.