Intel® oneAPI Data Analytics Library Developer Guide and Reference
A newer version of this document is available. Customers should click here to go to the newest version.
Batch Processing
Algorithm Parameters
The DBSCAN clustering algorithm has the following parameters:
Parameter  |  
        Default Valude  |  
        Description  |  
       
|---|---|---|
algorithmFPType  |  
        float  |  
        The floating-point type that the algorithm uses for intermediate computations. Can be float or double.  |  
       
method  |  
        defaultDense  |  
        Available methods for computation of DBSCAN algorithm: 
  |  
       
epsilon  |  
        Not applicable  |  
        The maximum distance between observations lying in the same neighborhood.  |  
       
minObservations  |  
        Not applicable  |  
        The number of observations in a neighborhood for an observation to be considered as a core one.  |  
       
memorySavingMode  |  
        false  |  
        If flag is set to false, all neighborhoods will be computed and stored prior to clustering. It will require up to  
            NOTE: 
            On GPU, the memorySavingMode flag can only be set to true. You will get an error if the flag is set to false. 
          |  
       
resultsToCompute  |  
        0  |  
        The 64-bit integer flag that specifies which extra characteristics of the DBSCAN algorithm to compute. Provide one of the following values to request a single characteristic or use bitwise OR to request a combination of the characteristics: 
  |  
       
Algorithm Input
The DBSCAN algorithm accepts the input described below. Pass the Input ID as a parameter to the methods that provide input for your algorithm. For more details, see Algorithms.
Input ID  |  
        Input  |  
       
|---|---|
data  |  
        Pointer to the  
            NOTE: 
            The input can be an object of any class derived from NumericTable. 
          |  
       
weights  |  
        Optional input. Pointer to the  
            NOTE: 
            The input can be an object of any class derived from NumericTable except PackedTriangularMatrix, PackedSymmetricMatrix. 
          By default all weights are equal to 1. 
            NOTE: 
            This parameter is ignored on GPU. 
          |  
       
Algorithm Output
The DBSCAN algorithms calculates the results described below. Pass the Result ID as a parameter to the methods that access the result of your algorithm. For more details, see Algorithms.
Result ID  |  
        Result  |  
       
|---|---|
assignments  |  
        Pointer to the  Noise observations have the assignment equal to -1.  |  
       
nClusters  |  
        Pointer to the   |  
       
coreIndices  |  
        Pointer to the numeric table with 1 column and arbitrary number of rows, containing indices of core observations.  |  
       
coreObservations  |  
        Pointer to the numeric table with p columns and arbitrary number of rows, containing core observations.  |  
       
 of additional memory, which in worst case can be 
. However, in general, performance may be better.
 numeric table with the data to be clustered.
 numeric table with weights of observations.
 numeric table with the total number of clusters found by the algorithm.