Unable to get root node error when using classifier
Unable to get root node error when using classifier
I have set up the classifier so that it creates the configuration in the trainer and accesses it in the processor but it says that it is unable to get the root node from the file I created in the trainer. Does this file need to be preexisting? I currently have it writing to a file I did not create before hand and am wondering if this is the problem.
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- Posts: 775
- Joined: Tue Dec 04, 2012 3:53 pm
- Location: INRIA Rennes, FRANCE
Re: Unable to get root node error when using classifier
Hi,
usually the classifier is created in one scenario and then used in another after the classifier has been saved by the first one. You can try to load the saved classifier with a text editor and see if it looks meaningful (can copy paste it here if you're not sure). Also, check that the classifier tutorials bundled with openvibe work (pick them from box-tutorials/, copy to somewhere with read access and try to run.
Hope this helps,
Jussi
usually the classifier is created in one scenario and then used in another after the classifier has been saved by the first one. You can try to load the saved classifier with a text editor and see if it looks meaningful (can copy paste it here if you're not sure). Also, check that the classifier tutorials bundled with openvibe work (pick them from box-tutorials/, copy to somewhere with read access and try to run.
Hope this helps,
Jussi
Re: Unable to get root node error when using classifier
I am not sure if the classifier is meaningful so I copied and pasted it below. I did run the example scenarios and they worked. Thank you for your help.
<OpenViBE-Scenario>
<Creator>OpenViBE</Creator>
<CreatorVersion>1.3.0</CreatorVersion>
<Boxes>
<Box>
<Identifier>(0x0000104d, 0x00004d02)</Identifier>
<Name>Confusion Matrix</Name>
<AlgorithmClassIdentifier>(0x1ab625da, 0x3b2502ce)</AlgorithmClassIdentifier>
<Inputs>
<Input>
<TypeIdentifier>(0x6f752dd0, 0x082a321e)</TypeIdentifier>
<Name>Targets</Name>
</Input>
<Input>
<TypeIdentifier>(0x6f752dd0, 0x082a321e)</TypeIdentifier>
<Name>Classification results</Name>
</Input>
</Inputs>
<Outputs>
<Output>
<TypeIdentifier>(0x544a003e, 0x6dcba5f6)</TypeIdentifier>
<Name>Confusion Matrix</Name>
</Output>
</Outputs>
<Settings>
<Setting>
<TypeIdentifier>(0x2cdb2f0b, 0x12f231ea)</TypeIdentifier>
<Name>Percentages</Name>
<DefaultValue>true</DefaultValue>
<Value>true</Value>
<Modifiability>false</Modifiability>
</Setting>
<Setting>
<TypeIdentifier>(0x2cdb2f0b, 0x12f231ea)</TypeIdentifier>
<Name>Sums</Name>
<DefaultValue>false</DefaultValue>
<Value>false</Value>
<Modifiability>false</Modifiability>
</Setting>
<Setting>
<TypeIdentifier>(0x2c132d6e, 0x44ab0d97)</TypeIdentifier>
<Name>Class 1</Name>
<DefaultValue>OVTK_StimulationId_Label_00</DefaultValue>
<Value>OVTK_StimulationId_Label_00</Value>
<Modifiability>false</Modifiability>
</Setting>
<Setting>
<TypeIdentifier>(0x2c132d6e, 0x44ab0d97)</TypeIdentifier>
<Name>Class 2</Name>
<DefaultValue>OVTK_StimulationId_Label_01</DefaultValue>
<Value>OVTK_StimulationId_Label_01</Value>
<Modifiability>false</Modifiability>
</Setting>
</Settings>
<Attributes>
<Attribute>
<Identifier>(0x1fa7a38f, 0x54edbe0b)</Identifier>
<Value>272.000000</Value>
</Attribute>
<Attribute>
<Identifier>(0x1fa963f5, 0x1a638cd4)</Identifier>
<Value>34</Value>
</Attribute>
<Attribute>
<Identifier>(0x207c9054, 0x3c841b63)</Identifier>
<Value>656.000000</Value>
</Attribute>
<Attribute>
<Identifier>(0x4e7b798a, 0x183beafb)</Identifier>
<Value>(0x05cf579a, 0x80d8b480)</Value>
</Attribute>
<Attribute>
<Identifier>(0x61d11811, 0x71e65362)</Identifier>
<Value></Value>
</Attribute>
<Attribute>
<Identifier>(0xad100179, 0xa3c984ab)</Identifier>
<Value>105</Value>
</Attribute>
<Attribute>
<Identifier>(0xc46b3d00, 0x3e0454e1)</Identifier>
<Value>(0x00000000, 0x0008743e)</Value>
</Attribute>
<Attribute>
<Identifier>(0xc73e83ec, 0xf855c5bc)</Identifier>
<Value>false</Value>
</Attribute>
<Attribute>
<Identifier>(0xc80ce8af, 0xf699f813)</Identifier>
<Value>1</Value>
</Attribute>
<Attribute>
<Identifier>(0xce18836a, 0x9c0eb403)</Identifier>
<Value>4</Value>
</Attribute>
<Attribute>
<Identifier>(0xcfad85b0, 0x7c6d841c)</Identifier>
<Value>2</Value>
</Attribute>
</Attributes>
</Box>
<Box>
<Identifier>(0x0000210e, 0x000063d9)</Identifier>
<Name>Classifier processor</Name>
<AlgorithmClassIdentifier>(0x5fe23d17, 0x95b0452c)</AlgorithmClassIdentifier>
<Inputs>
<Input>
<TypeIdentifier>(0x17341935, 0x152ff448)</TypeIdentifier>
<Name>Features</Name>
</Input>
<Input>
<TypeIdentifier>(0x6f752dd0, 0x082a321e)</TypeIdentifier>
<Name>Commands</Name>
</Input>
</Inputs>
<Outputs>
<Output>
<TypeIdentifier>(0x6f752dd0, 0x082a321e)</TypeIdentifier>
<Name>Labels</Name>
</Output>
<Output>
<TypeIdentifier>(0x544a003e, 0x6dcba5f6)</TypeIdentifier>
<Name>Hyperplane distance</Name>
</Output>
<Output>
<TypeIdentifier>(0x544a003e, 0x6dcba5f6)</TypeIdentifier>
<Name>Probability values</Name>
</Output>
</Outputs>
<Settings>
<Setting>
<TypeIdentifier>(0x330306dd, 0x74a95f98)</TypeIdentifier>
<Name>Filename to load configuration from</Name>
<DefaultValue></DefaultValue>
<Value>C:/Users/Vikram/Desktop/10th Grade/Science Fair/firstone</Value>
<Modifiability>false</Modifiability>
</Setting>
</Settings>
<Attributes>
<Attribute>
<Identifier>(0x1fa7a38f, 0x54edbe0b)</Identifier>
<Value>112.000000</Value>
</Attribute>
<Attribute>
<Identifier>(0x1fa963f5, 0x1a638cd4)</Identifier>
<Value>23</Value>
</Attribute>
<Attribute>
<Identifier>(0x207c9054, 0x3c841b63)</Identifier>
<Value>592.000000</Value>
</Attribute>
<Attribute>
<Identifier>(0x4e7b798a, 0x183beafb)</Identifier>
<Value>(0xa6c8e548, 0x9e3e405b)</Value>
</Attribute>
<Attribute>
<Identifier>(0xad100179, 0xa3c984ab)</Identifier>
<Value>120</Value>
</Attribute>
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<Identifier>(0xc46b3d00, 0x3e0454e1)</Identifier>
<Value>(0x00000000, 0x00069e7f)</Value>
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<Attribute>
<Identifier>(0xc73e83ec, 0xf855c5bc)</Identifier>
<Value>false</Value>
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<Attribute>
<Identifier>(0xc80ce8af, 0xf699f813)</Identifier>
<Value>3</Value>
</Attribute>
<Attribute>
<Identifier>(0xce18836a, 0x9c0eb403)</Identifier>
<Value>1</Value>
</Attribute>
<Attribute>
<Identifier>(0xcfad85b0, 0x7c6d841c)</Identifier>
<Value>2</Value>
</Attribute>
</Attributes>
</Box>
<Box>
<Identifier>(0x00004722, 0x00006d8c)</Identifier>
<Name>Matrix Display</Name>
<AlgorithmClassIdentifier>(0x54f0796d, 0x3ede2cc0)</AlgorithmClassIdentifier>
<Inputs>
<Input>
<TypeIdentifier>(0x544a003e, 0x6dcba5f6)</TypeIdentifier>
<Name>Matrix</Name>
</Input>
</Inputs>
<Settings>
<Setting>
<TypeIdentifier>(0x3d3c7c7f, 0xef0e7129)</TypeIdentifier>
<Name>Color gradient</Name>
<DefaultValue>0:2,36,58; 50:100,100,100; 100:83,17,20</DefaultValue>
<Value>0:2,36,58; 50:100,100,100; 100:83,17,20</Value>
<Modifiability>false</Modifiability>
</Setting>
<Setting>
<TypeIdentifier>(0x007deef9, 0x2f3e95c6)</TypeIdentifier>
<Name>Steps</Name>
<DefaultValue>100</DefaultValue>
<Value>100</Value>
<Modifiability>false</Modifiability>
</Setting>
<Setting>
<TypeIdentifier>(0x2cdb2f0b, 0x12f231ea)</TypeIdentifier>
<Name>Symetric min/max</Name>
<DefaultValue>false</DefaultValue>
<Value>false</Value>
<Modifiability>false</Modifiability>
</Setting>
<Setting>
<TypeIdentifier>(0x2cdb2f0b, 0x12f231ea)</TypeIdentifier>
<Name>Real time min/max</Name>
<DefaultValue>false</DefaultValue>
<Value>false</Value>
<Modifiability>false</Modifiability>
</Setting>
</Settings>
<Attributes>
<Attribute>
<Identifier>(0x1fa7a38f, 0x54edbe0b)</Identifier>
<Value>384.000000</Value>
</Attribute>
<Attribute>
<Identifier>(0x1fa963f5, 0x1a638cd4)</Identifier>
<Value>23</Value>
</Attribute>
<Attribute>
<Identifier>(0x207c9054, 0x3c841b63)</Identifier>
<Value>640.000000</Value>
</Attribute>
<Attribute>
<Identifier>(0x4e7b798a, 0x183beafb)</Identifier>
<Value>(0x4ff49bdb, 0x9dcf6788)</Value>
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<Attribute>
<Identifier>(0xad100179, 0xa3c984ab)</Identifier>
<Value>91</Value>
</Attribute>
<Attribute>
<Identifier>(0xc46b3d00, 0x3e0454e1)</Identifier>
<Value>(0x00000000, 0x000bdcb0)</Value>
</Attribute>
<Attribute>
<Identifier>(0xc73e83ec, 0xf855c5bc)</Identifier>
<Value>false</Value>
</Attribute>
<Attribute>
<Identifier>(0xce18836a, 0x9c0eb403)</Identifier>
<Value>4</Value>
</Attribute>
<Attribute>
<Identifier>(0xcfad85b0, 0x7c6d841c)</Identifier>
<Value>1</Value>
</Attribute>
</Attributes>
</Box>
<Box>
<Identifier>(0x00004c4f, 0x000019e4)</Identifier>
<Name>General statistics generator</Name>
<AlgorithmClassIdentifier>(0x83eda40b, 0x425fbffe)</AlgorithmClassIdentifier>
<Inputs>
<Input>
<TypeIdentifier>(0x5ba36127, 0x195feae1)</TypeIdentifier>
<Name>Signal</Name>
</Input>
<Input>
<TypeIdentifier>(0x6f752dd0, 0x082a321e)</TypeIdentifier>
<Name>Stimulations</Name>
</Input>
</Inputs>
<Settings>
<Setting>
<TypeIdentifier>(0x330306dd, 0x74a95f98)</TypeIdentifier>
<Name>Filename for saving</Name>
<DefaultValue>${Path_UserData}/statistics-dump.xml</DefaultValue>
<Value>${Path_UserData}/statistics-dump.xml</Value>
<Modifiability>false</Modifiability>
</Setting>
</Settings>
<Attributes>
<Attribute>
<Identifier>(0x1fa7a38f, 0x54edbe0b)</Identifier>
<Value>256.000000</Value>
</Attribute>
<Attribute>
<Identifier>(0x1fa963f5, 0x1a638cd4)</Identifier>
<Value>45</Value>
</Attribute>
<Attribute>
<Identifier>(0x207c9054, 0x3c841b63)</Identifier>
<Value>320.000000</Value>
</Attribute>
<Attribute>
<Identifier>(0x4e7b798a, 0x183beafb)</Identifier>
<Value>(0xf6674389, 0x42f4fe25)</Value>
</Attribute>
<Attribute>
<Identifier>(0xad100179, 0xa3c984ab)</Identifier>
<Value>169</Value>
</Attribute>
<Attribute>
<Identifier>(0xc46b3d00, 0x3e0454e1)</Identifier>
<Value>(0x00000000, 0x0013a92e)</Value>
</Attribute>
<Attribute>
<Identifier>(0xc67a01dc, 0x28ce06c1)</Identifier>
<Value></Value>
</Attribute>
<Attribute>
<Identifier>(0xc73e83ec, 0xf855c5bc)</Identifier>
<Value>false</Value>
</Attribute>
<Attribute>
<Identifier>(0xce18836a, 0x9c0eb403)</Identifier>
<Value>1</Value>
</Attribute>
<Attribute>
<Identifier>(0xcfad85b0, 0x7c6d841c)</Identifier>
<Value>2</Value>
</Attribute>
<Attribute>
<Identifier>(0xf191c1c8, 0xa0123976)</Identifier>
<Value></Value>
</Attribute>
</Attributes>
</Box>
<Box>
<Identifier>(0x00005fad, 0x00003802)</Identifier>
<Name>Classifier Accuracy Measure</Name>
<AlgorithmClassIdentifier>(0x48395ce7, 0x17d62550)</AlgorithmClassIdentifier>
<Inputs>
<Input>
<TypeIdentifier>(0x6f752dd0, 0x082a321e)</TypeIdentifier>
<Name>Targets</Name>
</Input>
<Input>
<TypeIdentifier>(0x6f752dd0, 0x082a321e)</TypeIdentifier>
<Name>Classifier 1</Name>
</Input>
</Inputs>
<Attributes>
<Attribute>
<Identifier>(0x1fa7a38f, 0x54edbe0b)</Identifier>
<Value>272.000000</Value>
</Attribute>
<Attribute>
<Identifier>(0x1fa963f5, 0x1a638cd4)</Identifier>
<Value>34</Value>
</Attribute>
<Attribute>
<Identifier>(0x207c9054, 0x3c841b63)</Identifier>
<Value>496.000000</Value>
</Attribute>
<Attribute>
<Identifier>(0x4e7b798a, 0x183beafb)</Identifier>
<Value>(0x8942cf6b, 0x91b31641)</Value>
</Attribute>
<Attribute>
<Identifier>(0x527ad68d, 0x16d746a0)</Identifier>
<Value></Value>
</Attribute>
<Attribute>
<Identifier>(0xad100179, 0xa3c984ab)</Identifier>
<Value>144</Value>
</Attribute>
<Attribute>
<Identifier>(0xc46b3d00, 0x3e0454e1)</Identifier>
<Value>(0x00000000, 0x00092cc3)</Value>
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<Attribute>
<Identifier>(0xc73e83ec, 0xf855c5bc)</Identifier>
<Value>false</Value>
</Attribute>
<Attribute>
<Identifier>(0xcfad85b0, 0x7c6d841c)</Identifier>
<Value>2</Value>
</Attribute>
<Attribute>
<Identifier>(0xfba64161, 0x65304e21)</Identifier>
<Value></Value>
</Attribute>
</Attributes>
</Box>
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<Link>
<Identifier>(0x00000f8c, 0x00000325)</Identifier>
<Source>
<BoxIdentifier>(0x0000210e, 0x000063d9)</BoxIdentifier>
<BoxOutputIndex>0</BoxOutputIndex>
</Source>
<Target>
<BoxIdentifier>(0x0000104d, 0x00004d02)</BoxIdentifier>
<BoxInputIndex>0</BoxInputIndex>
</Target>
<Attributes>
<Attribute>
<Identifier>(0x1b32c44c, 0x1905e0e9)</Identifier>
<Value>130</Value>
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<Attribute>
<Identifier>(0x358ae8b5, 0x0f8bacd1)</Identifier>
<Value>577</Value>
</Attribute>
<Attribute>
<Identifier>(0x3f0a3b27, 0x570913d2)</Identifier>
<Value>250</Value>
</Attribute>
<Attribute>
<Identifier>(0x6267b5c5, 0x676e3e42)</Identifier>
<Value>648</Value>
</Attribute>
</Attributes>
</Link>
<Link>
<Identifier>(0x00001d52, 0x00006ff7)</Identifier>
<Source>
<BoxIdentifier>(0x0000210e, 0x000063d9)</BoxIdentifier>
<BoxOutputIndex>0</BoxOutputIndex>
</Source>
<Target>
<BoxIdentifier>(0x00005fad, 0x00003802)</BoxIdentifier>
<BoxInputIndex>0</BoxInputIndex>
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<MessageLinks></MessageLinks>
<Comments></Comments>
<VisualisationTree>
<VisualisationWidget>
<Identifier>(0x000029d5, 0x00004c0a)</Identifier>
<Type>3</Type>
<ParentIdentifier>(0xffffffff, 0xffffffff)</ParentIdentifier>
<BoxIdentifier>(0x00005fad, 0x00003802)</BoxIdentifier>
<NumChildren>0</NumChildren>
</VisualisationWidget>
<VisualisationWidget>
<Identifier>(0x00005df7, 0x000049a4)</Identifier>
<Name>Default window</Name>
<Type>1</Type>
<ParentIdentifier>(0xffffffff, 0xffffffff)</ParentIdentifier>
<BoxIdentifier>(0xffffffff, 0xffffffff)</BoxIdentifier>
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<VisualisationWidget>
<Identifier>(0x00000d48, 0x00004189)</Identifier>
<Name>Default tab</Name>
<Type>2</Type>
<ParentIdentifier>(0x00005df7, 0x000049a4)</ParentIdentifier>
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<OpenViBE-Scenario>
<Creator>OpenViBE</Creator>
<CreatorVersion>1.3.0</CreatorVersion>
<Boxes>
<Box>
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<AlgorithmClassIdentifier>(0x1ab625da, 0x3b2502ce)</AlgorithmClassIdentifier>
<Inputs>
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<Input>
<TypeIdentifier>(0x6f752dd0, 0x082a321e)</TypeIdentifier>
<Name>Classification results</Name>
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<Outputs>
<Output>
<TypeIdentifier>(0x544a003e, 0x6dcba5f6)</TypeIdentifier>
<Name>Confusion Matrix</Name>
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<TypeIdentifier>(0x2c132d6e, 0x44ab0d97)</TypeIdentifier>
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<DefaultValue>OVTK_StimulationId_Label_00</DefaultValue>
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<Modifiability>false</Modifiability>
</Setting>
<Setting>
<TypeIdentifier>(0x2c132d6e, 0x44ab0d97)</TypeIdentifier>
<Name>Class 2</Name>
<DefaultValue>OVTK_StimulationId_Label_01</DefaultValue>
<Value>OVTK_StimulationId_Label_01</Value>
<Modifiability>false</Modifiability>
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<Box>
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<Name>Classifier processor</Name>
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<Inputs>
<Input>
<TypeIdentifier>(0x17341935, 0x152ff448)</TypeIdentifier>
<Name>Features</Name>
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<Input>
<TypeIdentifier>(0x6f752dd0, 0x082a321e)</TypeIdentifier>
<Name>Commands</Name>
</Input>
</Inputs>
<Outputs>
<Output>
<TypeIdentifier>(0x6f752dd0, 0x082a321e)</TypeIdentifier>
<Name>Labels</Name>
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<Output>
<TypeIdentifier>(0x544a003e, 0x6dcba5f6)</TypeIdentifier>
<Name>Hyperplane distance</Name>
</Output>
<Output>
<TypeIdentifier>(0x544a003e, 0x6dcba5f6)</TypeIdentifier>
<Name>Probability values</Name>
</Output>
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<Setting>
<TypeIdentifier>(0x330306dd, 0x74a95f98)</TypeIdentifier>
<Name>Filename to load configuration from</Name>
<DefaultValue></DefaultValue>
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<Modifiability>false</Modifiability>
</Setting>
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<Value>112.000000</Value>
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<Identifier>(0x1fa963f5, 0x1a638cd4)</Identifier>
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-
- Posts: 775
- Joined: Tue Dec 04, 2012 3:53 pm
- Location: INRIA Rennes, FRANCE
Re: Unable to get root node error when using classifier
Hi,
that is an openvibe scenario .xml. You cannot load a scenario to the Classifier Processor. The xml the classifier processor understands must be generated by a successful run of the Classifier Trainer box. The name and path of the generated file can be specified in the trainer box config and must not be the same as the scenario file.
Best,
Jussi
that is an openvibe scenario .xml. You cannot load a scenario to the Classifier Processor. The xml the classifier processor understands must be generated by a successful run of the Classifier Trainer box. The name and path of the generated file can be specified in the trainer box config and must not be the same as the scenario file.
Best,
Jussi