PLearn 0.1
|
00001 // -*- C++ -*- 00002 00003 // plearn_noblas_inc.h 00004 // 00005 // Copyright (C) 2006 Pascal Vincent 00006 // 00007 // Redistribution and use in source and binary forms, with or without 00008 // modification, are permitted provided that the following conditions are met: 00009 // 00010 // 1. Redistributions of source code must retain the above copyright 00011 // notice, this list of conditions and the following disclaimer. 00012 // 00013 // 2. Redistributions in binary form must reproduce the above copyright 00014 // notice, this list of conditions and the following disclaimer in the 00015 // documentation and/or other materials provided with the distribution. 00016 // 00017 // 3. The name of the authors may not be used to endorse or promote 00018 // products derived from this software without specific prior written 00019 // permission. 00020 // 00021 // THIS SOFTWARE IS PROVIDED BY THE AUTHORS ``AS IS'' AND ANY EXPRESS OR 00022 // IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES 00023 // OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN 00024 // NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, 00025 // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED 00026 // TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR 00027 // PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF 00028 // LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING 00029 // NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS 00030 // SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. 00031 // 00032 // This file is part of the PLearn library. For more information on the PLearn 00033 // library, go to the PLearn Web site at www.plearn.org 00034 00035 /* ******************************************************* 00036 * $Id: plearn_noblas_inc.h 6346 2006-10-24 17:02:02Z lamblin $ 00037 ******************************************************* */ 00038 00039 // Authors: Olivier Delalleau 00040 00047 #ifndef plearn_noblas_inc_INC 00048 #define plearn_noblas_inc_INC 00049 00050 /***************** 00051 * Miscellaneous * 00052 *****************/ 00053 #include <plearn/db/UCISpecification.h> 00054 #include <plearn/io/openUrl.h> 00055 #include <plearn/io/RPPath.h> 00056 #include <plearn/math/ManualBinner.h> 00057 #include <plearn/math/SoftHistogramBinner.h> 00058 #include <plearn/misc/ShellScript.h> 00059 #include <plearn/misc/Redirect.h> 00060 #include <plearn/misc/RunObject.h> 00061 #include <plearn_learners/misc/Grapher.h> 00062 #include <plearn_learners/misc/VariableSelectionWithDirectedGradientDescent.h> 00063 #include <plearn_learners/testers/PTester.h> 00064 #include <plearn/misc/HTMLHelpGenerator.h> 00065 00066 00067 /*********** 00068 * Command * 00069 ***********/ 00070 #include <commands/PLearnCommands/VMatCommand.h> 00071 #include <commands/PLearnCommands/AutoRunCommand.h> 00072 #include <commands/PLearnCommands/DiffCommand.h> 00073 #include <commands/PLearnCommands/FieldConvertCommand.h> 00074 #include <commands/PLearnCommands/HelpCommand.h> 00075 #include <commands/PLearnCommands/JulianDateCommand.h> 00076 #include <commands/PLearnCommands/KolmogorovSmirnovCommand.h> 00077 #include <commands/PLearnCommands/LearnerCommand.h> 00078 #include <commands/PLearnCommands/PairwiseDiffsCommand.h> 00079 #include <commands/PLearnCommands/ReadAndWriteCommand.h> 00080 #include <commands/PLearnCommands/RunCommand.h> 00081 #include <commands/PLearnCommands/ServerCommand.h> 00082 #include <commands/PLearnCommands/TestDependenciesCommand.h> 00083 #include <commands/PLearnCommands/TestDependencyCommand.h> 00084 #include <commands/PLearnCommands/StatsCommand.h> 00085 00086 // * extra stuff from Boost to generate help * 00087 //#include <commands/PLearnCommands/HTMLHelpCommand.h>//<! DEPRECATED (will disappear soon) 00088 00089 //#include <commands/PLearnCommands/TxtmatCommand.h> 00090 00091 00092 /************** 00093 * Dictionary * 00094 **************/ 00095 #include <plearn/dict/Dictionary.h> 00096 #include <plearn/dict/FileDictionary.h> 00097 #include <plearn/dict/VecDictionary.h> 00098 #include <plearn/dict/ConditionalDictionary.h> 00099 00100 /**************** 00101 * HyperCommand * 00102 ****************/ 00103 #include <plearn_learners/hyper/HyperOptimize.h> 00104 #include <plearn_learners/hyper/HyperRetrain.h> 00105 #include <plearn_learners/hyper/HyperSetOption.h> 00106 00107 /********** 00108 * Kernel * 00109 **********/ 00110 #include <plearn/ker/AdditiveNormalizationKernel.h> 00113 //#include <plearn/ker/BetaKernel.h> 00114 #include <plearn/ker/CosKernel.h> 00115 #include <plearn/ker/DistanceKernel.h> 00116 #include <plearn/ker/DotProductKernel.h> 00117 #include <plearn/ker/EpanechnikovKernel.h> 00118 #include <plearn/ker/GaussianKernel.h> 00119 #include <plearn/ker/GaussianDensityKernel.h> 00120 #include <plearn/ker/GeodesicDistanceKernel.h> 00121 #include <plearn/ker/IIDNoiseKernel.h> 00122 #include <plearn/ker/LinearARDKernel.h> 00123 #include <plearn/ker/NegOutputCostFunction.h> 00124 #include <plearn/ker/NeuralNetworkARDKernel.h> 00125 #include <plearn/ker/PolynomialKernel.h> 00126 #include <plearn/ker/RationalQuadraticARDKernel.h> 00127 #include <plearn/ker/SquaredExponentialARDKernel.h> 00128 #include <plearn/ker/SummationKernel.h> 00129 #include <plearn/ker/ThresholdedKernel.h> 00130 #include <plearn/ker/VMatKernel.h> 00131 #include <plearn/ker/DTWKernel.h> 00132 00133 /************* 00134 * Optimizer * 00135 *************/ 00136 #include <plearn/opt/AdaptGradientOptimizer.h> 00137 #include <plearn/opt/ConjGradientOptimizer.h> 00138 #include <plearn/opt/GradientOptimizer.h> 00139 00140 /**************** 00141 * OptionOracle * 00142 ****************/ 00143 #include <plearn_learners/hyper/CartesianProductOracle.h> 00144 #include <plearn_learners/hyper/EarlyStoppingOracle.h> 00145 #include <plearn_learners/hyper/ExplicitListOracle.h> 00146 #include <plearn_learners/hyper/OptimizeOptionOracle.h> 00147 00148 /************ 00149 * PLearner * 00150 ************/ 00151 00152 // Classifiers 00153 #include <plearn_learners/classifiers/BinaryStump.h> 00154 #include <plearn_learners/classifiers/ClassifierFromConditionalPDistribution.h> 00155 #include <plearn_learners/classifiers/ClassifierFromDensity.h> 00156 #include <plearn_learners/classifiers/KNNClassifier.h> 00157 //#include <plearn_learners/classifiers/SVMClassificationTorch.h> 00158 #include <plearn_learners/classifiers/MultiInstanceNNet.h> 00159 //#include <plearn_learners/classifiers/OverlappingAdaBoost.h> // Does not currently compile. 00160 #include <plearn_learners/classifiers/ToBagClassifier.h> 00161 00162 // Generic 00163 #include <plearn_learners/generic/AddCostToLearner.h> 00164 #include <plearn_learners/generic/AddLayersNNet.h> 00165 #include <plearn_learners/generic/BestAveragingPLearner.h> 00166 //#include <plearn_learners/generic/DistRepNNet.h> 00167 #include <plearn_learners/generic/NNet.h> 00168 #include <plearn_learners/generic/SelectInputSubsetLearner.h> 00169 #include <plearn_learners/generic/ChainedLearners.h> 00170 #include <plearn_learners/generic/StackedLearner.h> 00171 #include <plearn_learners/generic/TestingLearner.h> 00172 #include <plearn_learners/generic/TransformOutputLearner.h> 00173 #include <plearn_learners/generic/VPLPreprocessedLearner.h> 00174 #include <plearn_learners/generic/VPLPreprocessedLearner2.h> 00175 #include <plearn_learners/generic/VPLCombinedLearner.h> 00176 00177 // Hyper 00178 #include <plearn_learners/hyper/HyperLearner.h> 00179 00180 // Meta 00181 #include <plearn_learners/meta/AdaBoost.h> 00182 #include <plearn_learners/meta/MultiClassAdaBoost.h> 00183 #include <plearn_learners/meta/BaggingLearner.h> 00184 00185 // Regressors 00186 #include <plearn_learners/regressors/ConstantRegressor.h> 00187 #include <plearn_learners/regressors/CubicSpline.h> 00188 #include <plearn_learners/regressors/GaussianProcessRegressor.h> 00189 #include <plearn_learners/regressors/KernelRidgeRegressor.h> 00190 #include <plearn_learners/regressors/KNNRegressor.h> 00191 #include <plearn_learners/regressors/RankLearner.h> 00192 #include <plearn_learners/regressors/RegressorFromDistribution.h> 00193 #include <plearn_learners/regressors/RegressionTree.h> 00194 #include <plearn_learners/regressors/RegressionTreeMulticlassLeave.h> 00195 #include <plearn_learners/regressors/RegressionTreeMulticlassLeaveFast.h> 00196 #include <plearn_learners/regressors/RegressionTreeMulticlassLeaveProb.h> 00197 00198 // Unsupervised 00199 #include <plearn_learners/unsupervised/UniformizeLearner.h> 00200 00201 // PDistribution 00202 #include <plearn_learners/distributions/MixtureDistribution.h> 00203 #include <plearn_learners/distributions/SpiralDistribution.h> 00204 #include <plearn_learners/distributions/UniformDistribution.h> 00205 #include <plearn_learners/distributions/KernelDensityEstimator.h> 00206 00207 // Nearest-Neighbors 00208 #include <plearn_learners/nearest_neighbors/BallTreeNearestNeighbors.h> 00209 #include <plearn_learners/nearest_neighbors/ExhaustiveNearestNeighbors.h> 00210 #include <plearn_learners/nearest_neighbors/GenericNearestNeighbors.h> 00211 00212 // Experimental 00213 #include <plearn_learners_experimental/DeepFeatureExtractorNNet.h> 00214 00215 // Online 00216 #include <plearn_learners/online/ArgmaxModule.h> 00217 #include <plearn_learners/online/BackConvolution2DModule.h> 00218 #include <plearn_learners/online/ClassErrorCostModule.h> 00219 #include <plearn_learners/online/CombiningCostsModule.h> 00220 #include <plearn_learners/online/Convolution2DModule.h> 00221 #include <plearn_learners/online/CostModule.h> 00222 #include <plearn_learners/online/CrossEntropyCostModule.h> 00223 #include <plearn_learners/online/DeepBeliefNet.h> 00224 #include <plearn_learners/online/ForwardModule.h> 00225 #include <plearn_learners/online/GradNNetLayerModule.h> 00226 #include <plearn_learners/online/IdentityModule.h> 00227 #include <plearn_learners/online/InferenceRBM.h> 00228 #include <plearn_learners/online/LayerCostModule.h> 00229 #include <plearn_learners/online/LinearCombinationModule.h> 00230 #include <plearn_learners/online/LinearFilterModule.h> 00231 #include <plearn_learners/online/LogaddOnBagsModule.h> 00232 #include <plearn_learners/online/MatrixModule.h> 00233 #include <plearn_learners/online/MaxSubsampling2DModule.h> 00234 #include <plearn_learners/online/ModuleLearner.h> 00235 #include <plearn_learners/online/ModulesLearner.h> 00236 #include <plearn_learners/online/ModuleStackModule.h> 00237 #include <plearn_learners/online/ModuleTester.h> 00238 #include <plearn_learners/online/NetworkModule.h> 00239 #include <plearn_learners/online/NLLCostModule.h> 00240 #include <plearn_learners/online/OnlineLearningModule.h> 00241 #include <plearn_learners/online/ProcessInputCostModule.h> 00242 #include <plearn_learners/online/RBMBinomialLayer.h> 00243 #include <plearn_learners/online/RBMClassificationModule.h> 00244 #include <plearn_learners/online/RBMConnection.h> 00245 #include <plearn_learners/online/RBMConv2DConnection.h> 00246 #include <plearn_learners/online/RBMGaussianLayer.h> 00247 #include <plearn_learners/online/RBMLayer.h> 00248 #include <plearn_learners/online/RBMLocalMultinomialLayer.h> 00249 #include <plearn_learners/online/RBMMatrixConnection.h> 00250 #include <plearn_learners/online/RBMMatrixTransposeConnection.h> 00251 #include <plearn_learners/online/RBMMixedConnection.h> 00252 #include <plearn_learners/online/RBMMixedLayer.h> 00253 #include <plearn_learners/online/RBMModule.h> 00254 #include <plearn_learners/online/RBMMultinomialLayer.h> 00255 #include <plearn_learners/online/RBMSparse1DMatrixConnection.h> 00256 #include <plearn_learners/online/RBMTrainer.h> 00257 #include <plearn_learners/online/RBMTruncExpLayer.h> 00258 #include <plearn_learners/online/ScaleGradientModule.h> 00259 #include <plearn_learners/online/ShuntingNNetLayerModule.h> 00260 #include <plearn_learners/online/SoftmaxModule.h> 00261 #include <plearn_learners/online/SoftmaxNLLCostModule.h> 00262 #include <plearn_learners/online/SplitModule.h> 00263 #include <plearn_learners/online/SquaredErrorCostModule.h> 00264 #include <plearn_learners/online/BinarizeModule.h> 00265 #include <plearn_learners/online/StackedAutoassociatorsNet.h> 00266 #include <plearn_learners/online/Subsampling2DModule.h> 00267 #include <plearn_learners/online/Supersampling2DModule.h> 00268 #include <plearn_learners/online/TanhModule.h> 00269 00270 /************ 00271 * Splitter * 00272 ************/ 00273 #include <plearn/vmat/BinSplitter.h> 00274 #include <plearn/vmat/BootstrapSplitter.h> 00275 #include <plearn/vmat/ClassSeparationSplitter.h> 00276 #include <plearn/vmat/ConcatSetsSplitter.h> 00277 #include <plearn/vmat/DBSplitter.h> 00278 #include <plearn/vmat/ExplicitSplitter.h> 00279 #include <plearn/vmat/FilterSplitter.h> 00280 #include <plearn/vmat/FractionSplitter.h> 00281 #include <plearn/vmat/KFoldSplitter.h> 00282 #include <plearn/vmat/NoSplitSplitter.h> 00283 #include <plearn/vmat/MultiTaskSeparationSplitter.h> 00284 #include <plearn/vmat/RepeatSplitter.h> 00285 #include <plearn/vmat/SelectSetsSplitter.h> 00286 #include <plearn/vmat/SourceVMatrixSplitter.h> 00287 #include <plearn/vmat/StackedSplitter.h> 00288 #include <plearn/vmat/TestInTrainSplitter.h> 00289 #include <plearn/vmat/ToBagSplitter.h> 00290 #include <plearn/vmat/TrainTestSplitter.h> 00291 #include <plearn/vmat/TrainValidTestSplitter.h> 00292 00293 /************ 00294 * Variable * 00295 ************/ 00296 #include <plearn/var/MatrixElementsVariable.h> 00297 00298 /********************* 00299 * VecStatsCollector * 00300 *********************/ 00301 #include <plearn/math/LiftStatsCollector.h> 00302 00303 /*********** 00304 * VMatrix * 00305 ***********/ 00306 #include <plearn/vmat/AddMissingVMatrix.h> 00307 #include <plearn/vmat/AddBagInformationVMatrix.h> 00308 #include <plearn/vmat/AppendNeighborsVMatrix.h> 00309 #include <plearn/vmat/AsciiVMatrix.h> 00310 #include <plearn/vmat/AutoVMatrix.h> 00311 #include <plearn/vmat/AutoVMatrixSaveSource.h> 00312 #include <plearn/vmat/BootstrapVMatrix.h> 00313 #include <plearn/vmat/CenteredVMatrix.h> 00314 #include <plearn/vmat/ClassSubsetVMatrix.h> 00315 #include <plearn/vmat/CompactVMatrix.h> 00316 #include <plearn/vmat/CompactFileVMatrix.h> 00317 #include <plearn/vmat/CompressedVMatrix.h> 00318 #include <plearn/vmat/CumVMatrix.h> 00319 #include <plearn/vmat/ConcatColumnsVMatrix.h> 00320 #include <plearn/vmat/ConstantVMatrix.h> 00321 #include <plearn/vmat/DatedJoinVMatrix.h> 00322 // #include <plearn/vmat/DictionaryVMatrix.h> 00323 #include <plearn/vmat/DisregardRowsVMatrix.h> 00324 #include <plearn/vmat/DichotomizeVMatrix.h> 00325 #include <plearn/vmat/BinaryNumbersVMatrix.h> 00326 #include <plearn/vmat/ExtractNNetParamsVMatrix.h> 00327 #include <plearn/vmat/FilteredVMatrix.h> 00328 #include <plearn/vmat/FinancePreprocVMatrix.h> 00329 #include <plearn/vmat/GaussianizeVMatrix.h> 00330 #include <plearn/vmat/GeneralizedOneHotVMatrix.h> 00331 #include <plearn/vmat/GetInputVMatrix.h> 00332 #include <plearn/vmat/GramVMatrix.h> 00333 #include <plearn/vmat/IndexedVMatrix.h> 00334 #include <plearn/vmat/JulianizeVMatrix.h> 00335 #include <plearn/vmat/KNNVMatrix.h> 00336 #include <plearn/vmat/KNNImputationVMatrix.h> 00337 // Commented out because triggers WordNet, which does not work really fine yet. 00338 //#include <plearn/vmat/LemmatizeVMatrix.h> 00339 #include <plearn/vmat/LIBSVMSparseVMatrix.h> 00340 #include <plearn/vmat/LocalNeighborsDifferencesVMatrix.h> 00341 #include <plearn/vmat/LocallyPrecomputedVMatrix.h> 00342 #include <plearn/vmat/MeanImputationVMatrix.h> 00343 #include <plearn/vmat/MemoryVMatrixNoSave.h> 00344 #include <plearn/vmat/MissingInstructionVMatrix.h> 00345 #include <plearn/vmat/MixtureVMatrix.h> 00346 //#include <plearn/vmat/MixUnlabeledNeighbourVMatrix.h> 00347 #include <plearn/vmat/MultiInstanceVMatrix.h> 00348 #include <plearn/vmat/MultiTargetOneHotVMatrix.h> 00349 #include <plearn/vmat/MultiToUniInstanceSelectRandomVMatrix.h> 00350 #include <plearn/vmat/OneHotVMatrix.h> 00351 #include <plearn/vmat/PLearnerOutputVMatrix.h> 00352 #include <plearn/vmat/PairsVMatrix.h> 00353 #include <plearn/vmat/PrecomputedVMatrix.h> 00354 #include <plearn/vmat/ProcessDatasetVMatrix.h> 00355 #include <plearn/vmat/ProcessingVMatrix.h> 00356 #include <plearn/vmat/ProcessSymbolicSequenceVMatrix.h> 00357 #include <plearn/vmat/PutSubVMatrix.h> 00358 #include <plearn/vmat/RandomSamplesVMatrix.h> 00359 #include <plearn/vmat/RandomSamplesFromVMatrix.h> 00360 #include <plearn/vmat/RankedVMatrix.h> 00361 #include <plearn/vmat/RepeatVMatrix.h> 00362 #include <plearn/vmat/RegularGridVMatrix.h> 00363 #include <plearn/vmat/RemoveDuplicateVMatrix.h> 00364 #include <plearn/vmat/ReorderByMissingVMatrix.h> 00365 #include <plearn/vmat/ReplicateSamplesVMatrix.h> 00366 //#include <plearn/vmat/SelectAttributsSequenceVMatrix.h> 00367 #include <plearn/vmat/SelectRowsMultiInstanceVMatrix.h> 00368 #include <plearn/vmat/ShuffleColumnsVMatrix.h> 00369 #include <plearn/vmat/SortRowsVMatrix.h> 00370 #include <plearn/vmat/SparseVMatrix.h> 00371 #include <plearn/vmat/SplitWiseValidationVMatrix.h> 00372 #include <plearn/vmat/StochasticBinarizeVMatrix.h> 00373 #include <plearn/vmat/SubInputVMatrix.h> 00374 #include <plearn/vmat/TemporaryDiskVMatrix.h> 00375 #include <plearn/vmat/TemporaryFileVMatrix.h> 00376 #include <plearn/vmat/TextFilesVMatrix.h> 00377 #include <plearn/vmat/ThresholdVMatrix.h> 00378 #include <plearn/vmat/TransposeVMatrix.h> 00379 #include <plearn/vmat/UCIDataVMatrix.h> 00380 #include <plearn/vmat/UniformizeVMatrix.h> 00381 #include <plearn/vmat/VariableDeletionVMatrix.h> 00382 #include <plearn/vmat/ViewSplitterVMatrix.h> 00383 #include <plearn/vmat/VMatrixFromDistribution.h> 00384 00385 00386 00387 // **** Require LAPACK and BLAS 00388 00389 // Unsupervised/KernelProjection 00390 //#include <plearn_learners/unsupervised/Isomap.h> 00391 //#include <plearn_learners/unsupervised/KernelPCA.h> 00392 //#include <plearn_learners/unsupervised/LLE.h> 00393 //#include <plearn_learners/unsupervised/PCA.h> 00394 //#include <plearn_learners/unsupervised/SpectralClustering.h> 00395 00396 // Kernels 00397 //#include <plearn/ker/LLEKernel.h> 00398 //#include <plearn/ker/ReconstructionWeightsKernel.h> 00399 00400 // Regressors 00401 //#include <plearn_learners/regressors/LinearRegressor.h> 00402 //#include <plearn_learners/regressors/PLS.h> 00403 00404 // PDistribution 00405 //#include <plearn_learners/distributions/GaussianDistribution.h> 00406 //#include <plearn_learners/distributions/GaussMix.h> 00407 //#include <plearn_learners/distributions/RandomGaussMix.h> 00408 //#include <plearn_learners/distributions/ParzenWindow.h> 00409 //#include <plearn_learners/distributions/ManifoldParzen2.h> 00410 00411 // Experimental 00412 //#include <plearn_learners_experimental/LinearInductiveTransferClassifier.h> 00413 00414 // SurfaceTemplate 00415 // #include <plearn_learners_experimental/SurfaceTemplate/SurfaceTemplateLearner.h> 00416 00417 00418 #endif 00419 00420 00421 /* 00422 Local Variables: 00423 mode:c++ 00424 c-basic-offset:4 00425 c-file-style:"stroustrup" 00426 c-file-offsets:((innamespace . 0)(inline-open . 0)) 00427 indent-tabs-mode:nil 00428 fill-column:79 00429 End: 00430 */ 00431 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :