Changeset 7694 for trunk/sources/HeuristicLab.Algorithms.DataAnalysis
- Timestamp:
- 04/02/12 23:44:17 (13 years ago)
- Location:
- trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4
- Files:
-
- 3 edited
Legend:
- Unmodified
- Added
- Removed
-
trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/HeuristicLab.Algorithms.DataAnalysis-3.4.csproj
r7294 r7694 101 101 </PropertyGroup> 102 102 <ItemGroup> 103 <Reference Include="ALGLIB-3. 4.0, Version=3.4.0.0, Culture=neutral, PublicKeyToken=ba48961d6f65dcec, processorArchitecture=MSIL">104 <HintPath>..\..\bin\ALGLIB-3. 4.0.dll</HintPath>103 <Reference Include="ALGLIB-3.5.0, Version=3.5.0.0, Culture=neutral, PublicKeyToken=ba48961d6f65dcec, processorArchitecture=MSIL"> 104 <HintPath>..\..\bin\ALGLIB-3.5.0.dll</HintPath> 105 105 <Private>False</Private> 106 106 </Reference> -
trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkEnsembleModel.cs
r7259 r7694 63 63 : base(original, cloner) { 64 64 mlpEnsemble = new alglib.mlpensemble(); 65 mlpEnsemble.innerobj.columnmeans = (double[])original.mlpEnsemble.innerobj.columnmeans.Clone(); 66 mlpEnsemble.innerobj.columnsigmas = (double[])original.mlpEnsemble.innerobj.columnsigmas.Clone(); 67 mlpEnsemble.innerobj.dfdnet = (double[])original.mlpEnsemble.innerobj.dfdnet.Clone(); 68 mlpEnsemble.innerobj.ensemblesize = original.mlpEnsemble.innerobj.ensemblesize; 69 mlpEnsemble.innerobj.issoftmax = original.mlpEnsemble.innerobj.issoftmax; 70 mlpEnsemble.innerobj.neurons = (double[])original.mlpEnsemble.innerobj.neurons.Clone(); 71 mlpEnsemble.innerobj.nin = original.mlpEnsemble.innerobj.nin; 72 mlpEnsemble.innerobj.nout = original.mlpEnsemble.innerobj.nout; 73 mlpEnsemble.innerobj.postprocessing = original.mlpEnsemble.innerobj.postprocessing; 74 mlpEnsemble.innerobj.serializedlen = original.mlpEnsemble.innerobj.serializedlen; 75 mlpEnsemble.innerobj.serializedmlp = (double[])original.mlpEnsemble.innerobj.serializedmlp.Clone(); 76 mlpEnsemble.innerobj.structinfo = (int[])original.mlpEnsemble.innerobj.structinfo.Clone(); 77 mlpEnsemble.innerobj.tmpmeans = (double[])original.mlpEnsemble.innerobj.tmpmeans.Clone(); 78 mlpEnsemble.innerobj.tmpsigmas = (double[])original.mlpEnsemble.innerobj.tmpsigmas.Clone(); 79 mlpEnsemble.innerobj.tmpweights = (double[])original.mlpEnsemble.innerobj.tmpweights.Clone(); 80 mlpEnsemble.innerobj.wcount = original.mlpEnsemble.innerobj.wcount; 81 mlpEnsemble.innerobj.weights = (double[])original.mlpEnsemble.innerobj.weights.Clone(); 82 mlpEnsemble.innerobj.y = (double[])original.mlpEnsemble.innerobj.y.Clone(); 65 string serializedEnsemble; 66 alglib.mlpeserialize(original.mlpEnsemble, out serializedEnsemble); 67 alglib.mlpeunserialize(serializedEnsemble, out this.mlpEnsemble); 83 68 targetVariable = original.targetVariable; 84 69 allowedInputVariables = (string[])original.allowedInputVariables.Clone(); … … 168 153 #region persistence 169 154 [Storable] 155 private string MultiLayerPerceptronEnsembleNetwork { 156 get { 157 string serializedNetwork; 158 alglib.mlpeserialize(this.mlpEnsemble, out serializedNetwork); 159 return serializedNetwork; 160 } 161 set { 162 alglib.mlpeunserialize(value, out this.mlpEnsemble); 163 } 164 } 165 166 [Storable] 170 167 private double[] MultiLayerPerceptronEnsembleColumnMeans { 171 get { 172 return mlpEnsemble.innerobj.columnmeans; 173 } 168 get { return mlpEnsemble.innerobj.columnmeans; } 174 169 set { 175 170 mlpEnsemble.innerobj.columnmeans = value; 171 mlpEnsemble.innerobj.network.columnmeans = value; 176 172 } 177 173 } 178 174 [Storable] 179 175 private double[] MultiLayerPerceptronEnsembleColumnSigmas { 180 get { 181 return mlpEnsemble.innerobj.columnsigmas; 182 } 176 get { return mlpEnsemble.innerobj.columnsigmas; } 183 177 set { 184 178 mlpEnsemble.innerobj.columnsigmas = value; 185 } 186 } 187 [Storable] 179 mlpEnsemble.innerobj.network.columnsigmas = value; 180 } 181 } 182 [Storable(AllowOneWay = true)] 188 183 private double[] MultiLayerPerceptronEnsembleDfdnet { 189 get { 190 return mlpEnsemble.innerobj.dfdnet; 191 } 192 set { 193 mlpEnsemble.innerobj.dfdnet = value; 184 set { 185 mlpEnsemble.innerobj.network.dfdnet = value; 194 186 } 195 187 } 196 188 [Storable] 197 189 private int MultiLayerPerceptronEnsembleSize { 198 get { 199 return mlpEnsemble.innerobj.ensemblesize; 200 } 190 get { return mlpEnsemble.innerobj.ensemblesize; } 201 191 set { 202 192 mlpEnsemble.innerobj.ensemblesize = value; 203 } 204 } 205 [Storable] 206 private bool MultiLayerPerceptronEnsembleIsSoftMax { 207 get { 208 return mlpEnsemble.innerobj.issoftmax; 209 } 210 set { 211 mlpEnsemble.innerobj.issoftmax = value; 212 } 213 } 214 [Storable] 193 mlpEnsemble.innerobj.ensemblesize = value; 194 } 195 } 196 [Storable(AllowOneWay = true)] 215 197 private double[] MultiLayerPerceptronEnsembleNeurons { 216 get { 217 return mlpEnsemble.innerobj.neurons; 218 } 219 set { 220 mlpEnsemble.innerobj.neurons = value; 221 } 222 } 223 [Storable] 224 private int MultiLayerPerceptronEnsembleNin { 225 get { 226 return mlpEnsemble.innerobj.nin; 227 } 228 set { 229 mlpEnsemble.innerobj.nin = value; 230 } 231 } 232 [Storable] 233 private int MultiLayerPerceptronEnsembleNout { 234 get { 235 return mlpEnsemble.innerobj.nout; 236 } 237 set { 238 mlpEnsemble.innerobj.nout = value; 239 } 240 } 241 [Storable] 242 private bool MultiLayerPerceptronEnsemblePostprocessing { 243 get { 244 return mlpEnsemble.innerobj.postprocessing; 245 } 246 set { 247 mlpEnsemble.innerobj.postprocessing = value; 248 } 249 } 250 [Storable] 251 private int MultiLayerPerceptronEnsembleSerializedLen { 252 get { 253 return mlpEnsemble.innerobj.serializedlen; 254 } 255 set { 256 mlpEnsemble.innerobj.serializedlen = value; 257 } 258 } 259 [Storable] 198 set { mlpEnsemble.innerobj.network.neurons = value; } 199 } 200 [Storable(AllowOneWay = true)] 260 201 private double[] MultiLayerPerceptronEnsembleSerializedMlp { 261 get { 262 return mlpEnsemble.innerobj.serializedmlp; 263 } 264 set { 265 mlpEnsemble.innerobj.serializedmlp = value; 266 } 267 } 268 [Storable] 202 set { 203 mlpEnsemble.innerobj.network.dfdnet = value; 204 } 205 } 206 [Storable(AllowOneWay = true)] 269 207 private int[] MultiLayerPerceptronStuctinfo { 270 get { 271 return mlpEnsemble.innerobj.structinfo; 272 } 273 set { 274 mlpEnsemble.innerobj.structinfo = value; 275 } 276 } 277 [Storable] 278 private double[] MultiLayerPerceptronEnsembleTmpMeans { 279 get { 280 return mlpEnsemble.innerobj.tmpmeans; 281 } 282 set { 283 mlpEnsemble.innerobj.tmpmeans = value; 284 } 285 } 286 [Storable] 287 private double[] MultiLayerPerceptronEnsembleTmpSigmas { 288 get { 289 return mlpEnsemble.innerobj.tmpsigmas; 290 } 291 set { 292 mlpEnsemble.innerobj.tmpsigmas = value; 293 } 294 } 295 [Storable] 296 private double[] MultiLayerPerceptronEnsembleTmpWeights { 297 get { 298 return mlpEnsemble.innerobj.tmpweights; 299 } 300 set { 301 mlpEnsemble.innerobj.tmpweights = value; 302 } 303 } 304 [Storable] 305 private int MultiLayerPerceptronEnsembleWCount { 306 get { 307 return mlpEnsemble.innerobj.wcount; 308 } 309 set { 310 mlpEnsemble.innerobj.wcount = value; 208 set { 209 mlpEnsemble.innerobj.network.structinfo = value; 311 210 } 312 211 } … … 319 218 set { 320 219 mlpEnsemble.innerobj.weights = value; 220 mlpEnsemble.innerobj.network.weights = value; 321 221 } 322 222 } … … 328 228 set { 329 229 mlpEnsemble.innerobj.y = value; 230 mlpEnsemble.innerobj.network.y = value; 330 231 } 331 232 } -
trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/Plugin.cs.frame
r7294 r7694 28 28 [Plugin("HeuristicLab.Algorithms.DataAnalysis", "Provides wrappers for data analysis algorithms implemented in external libraries (linear regression, linear discriminant analysis, k-means clustering, support vector classification and regression)", "3.4.2.$WCREV$")] 29 29 [PluginFile("HeuristicLab.Algorithms.DataAnalysis-3.4.dll", PluginFileType.Assembly)] 30 [PluginDependency("HeuristicLab.ALGLIB", "3. 4.0")]30 [PluginDependency("HeuristicLab.ALGLIB", "3.5.0")] 31 31 [PluginDependency("HeuristicLab.Collections", "3.3")] 32 32 [PluginDependency("HeuristicLab.Common", "3.3")]
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