Unhandled exception in Kdtree KNN on in memory data

[mchinmay]

I am trying to use kdtree_knn_classification to do a 2d  k-nearest neighbour search on in-memory data. However i am getting an unhandled exception in the algorithm.compute() function.    Attached is my code snippet.  Is something wrong with my usage? Unfortunately i am not able to figure out from the documentation and the examples. Please help!  I am using daal 2021.1.1

[RaeesaM_Intel]

Hi,

Thank you for posting in Intel® oneAPI Data Analytics Library & Intel® Data Analytics Acceleration Library Forum.

Please share the operating system details.

Have you tried running the kdtree_knn_dense_batch sample of daal 2021.1.1 available with oneAPI base toolkit on linux . We were able to run it successfully without any issues, so the error you mentioned might be code related.

Here are the steps to build and run that sample using c++ compiler on linux:

1)     Setting up oneAPI environment via setvars.sh script:

source <install_directory>/setvars.sh

2)     DAAL kdtree sample is present in the below folder:

<install_directory>/dal/2021.1.1/examples/daal/cpp/source/k_nearest_neighbors/

3)     Use the makefile to build and run the DAAL examples, You can try any of the below commands:

cd <install_directory>/dal/2021.1.1/examples/daal/cpp/

4)     make libintel64 example=kdtree_knn_ dense_batch

[Now, it will build by Intel(R) oneAPI DPC++ Compiler (as default) and run pca example for 64-bit applications and do static linking]

OR

make sointel64 example= kdtree_knn_ dense_batch

[build by Intel(R) oneAPI Compiler (as default) and run all examples for Intel(R)64 processor family applications, dynamic linking

Please refer the following link for further details :

https://oneapi-src.github.io/oneDAL/getstarted.html#

https://software.intel.com/content/www/us/en/develop/documentation/get-started-intel-oneapi-data-analytics-library/top.html

Get back to us in case of any issues.

Thank you,

Raeesa

[mchinmay]

Hi,

Thanks for your reply.

I am using windows 10 enterprise and visual studio17 version 15.9.13.

Thanks

[AlexanderAndreev · Accepted solution]

Hi,

Instead of

algorithm.parameter.nClasses = 1;

use

algorithm.parameter.resultsToEvaluate = classifier::none;
algorithm.parameter.resultsToCompute = kdtree_knn_classification::computeDistances | kdtree_knn_classification::computeIndicesOfNeighbors;

and delete line

algorithm.input.set(classifier::training::labels, trainLabel);

to enable plain knn search without classification. Despite on your task, you might drop distances (kdtree_knn_classification::computeDistances) or indices (kdtree_knn_classification::computeIndicesOfNeighbors).

If classification is also needed, return label input line, delete line with resultsToEvaluate and add nClasses > 1:

algorithm.parameter.nClasses = nClasses;

Kind regards,

Alexander.

[mchinmay]

Hi Alexander,

Thanks for your solution.  Setting algorithm.parameter.resultsToEvaluate = classifier::none worked for me.

[RaeesaM_Intel]

Hi,

Glad to know that your issue got resolved. We are discontinuing monitoring this thread.Please raise a new thread in case of any further issues.

Thanks,

Raeesa