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Library Layout and Organization
Matteo Santoro edited this page Jul 1, 2013
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The GURLS module is composed of the following files and directories:
- gurls.m, implementing the GURLS core
- defopt.m, a function used to build a default options' structure
- demo, a directory containg the demos and the data
- quickandirty, a folder containing 2 functions for fast GURLS usage
- utils, a directory containing utility functions
- tasks directory and files, where the available tasks are listed in the table below
| Task category | Description | Available tasks |
|---|---|---|
| split | Splits data into one or more pair of training and validation sets | ho |
| paramsel | Performs selection of the regularization parameter lambda and, if using Gaussian kernel, also of the kernel parameter sigma | fixlambda, loocvprimal, loocvdual, hoprimal, hodual, siglam, siglamho, bfprimal, bfdual, calibratesgd, hoprimalr, hodualr, horandfeats, gpregrLambdaGrid, gpregrSigLambGrid, loogpregr, hogpregr, siglamhogpregr, siglamloogpregr, |
| kernel | Builds the symmetric kernel matrix to be used for training | chisquared, linear, load, randfeats, rbf |
| rls | Computes the optimizer | primal, dual, auto, pegasos, primalr, dualr, randfeats, gpregr |
| predkernel | Builds the train-test kernel matrix | traintest |
| pred | Predicts the labels | primal, dual, randfeats, gpregr |
| perf | Assess prediction performance | macroavg, precrec, rmse |
| conf | Computes a confidence for the highest scoring class | maxscore, gap, boltzmangap, boltzman |
The GURLS++ module is composed of the following directories:
- include, directory containing the headers of the GURLS++ core and tasks, and the implementation of template classes and methods
- src, directory containing the implementation of the non template classes and methods
- demo, containing the demos
- data, containing examples of data
- doc, containing the documentation (after running doxygen)
| Task category | Description | Class name | Available subclasses (tasks) |
|---|---|---|---|
| split | Splits data into one or more pair of training and validation sets | Split | Ho |
| paramsel | Performs selection of the regularization parameter lambda and, if using Gaussian kernel, also of the kernel parameter sigma | ParamSelection | LoocvDual, LoocvPrimal, HoDual, HoPrimal, SiglamHo, Siglam, FixLambda FixSigLam, HoPrimalr, HoDualr, LooGPRegr, HoGPRegr, SigLamLooGPRegr, SigLamHoGPRegr, CalibrateSGD |
| kernel | Builds the symmetric kernel matrix to be used for training | Kernel | ChisquaredKernel, LinearKernel, RBFKernel |
| rls | Computes the optimizer | Optimizer | RLSPrimal, RLSDual, RLSAuto, RLSPegasos, RLSPrimalr, RLSDualr, RLSGPRegr, RLSPrimalRecInit, RLSPrimalRecUpdate |
| predkernel | Builds the train-test kernel matrix | PredKernel | TrainTest |
| pred | Predicts the labels | Prediction | PredPrimal, PredDual, PredGPRegr |
| perf | Assess prediction performance | Performance | MacroAvg, PrecisionRecall, Rmse |
| conf | Confidence | Computes a confidence for the highest scoring class | ConfMaxScore, ConfGap, ConfBoltzmanGap, ConfBoltzman |
The GURLS module is composed of the following files and directories:
- bgurls.m, implementing the bGURLS core
- bigdefopt.m, a function used to build a default options' structure
- demo, a directory containg the demos and the data
- utils, a directory containing utility functions
- adm, a directory containing utility functions for bigarrays and distributed computing management
- tasks directory and files, where the available tasks are listed in the table below
| Task category | Description | Available tasks |
|---|---|---|
| bigparamsel | performs selection of the regularization parameter lambda and | hoprimal, calibratesgd, dhoprimal, |
| bigrls | Computes the optimizer | primal, pegasos, dprimal |
| bigpred | Predicts the labels | primal |
| bigperf | Assess prediction performance | macroavg |
The bGURLS++ module is composed of the following directories:
- include, directory containing the headers of the bGURLS++ core and tasks, and the implementation of template classes and methods
- src, directory containing the implementation of the non template classes and methods
- demo, containing the demos
- data, containing examples of data
- doc, containing the documentation (after running doxygen)
| Task category | Description | Class name | Available subclasses (tasks) |
|---|---|---|---|
| bigsplit | Splits data into one or more pair of training and validation sets | BigSplit | Ho |
| bigparamsel | performs selection of the regularization parameter lambda | BigParamSelection | HoPrimal |
| bigrls | Computes the optimizer | BigOptimizer | RLSPrimal |
| bigpred | Predicts the labels | BigPrediction | PredPrimal |
| bigperf | BigPerformance | Assess prediction performance | MacroAvg |