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A newer version of this document is available.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.
Basic Statistics
Basic statistics algorithm computes the following set of quantitative dataset characteristics:
minimums/maximums
sums
means
sums of squares
sums of squared differences from the means
second order raw moments
variances
standard deviations
variations
Operation  |  
       Computational methods  |  
       Programming Interface  |  
      ||
Mathematical formulation
Computing
Given a set X of np-dimensional feature vectors 
, the problem is to compute the following sample characteristics for each feature in the data set:
Statistic  |  
        Definition  |  
       
|---|---|
Minimum  |  
        
  |  
       
Maximum  |  
        
  |  
       
Sum  |  
        
  |  
       
Sum of squares  |  
        
  |  
       
Means  |  
        
  |  
       
Second order raw moment  |  
        
  |  
       
Sum of squared difference from the means  |  
        
  |  
       
Variance  |  
        
  |  
       
Standard deviation  |  
        
  |  
       
Variation coefficient  |  
        
  |  
       
Computation method: dense
The method computes the basic statistics for each feature in the data set.
Programming Interface
Refer to API Reference: Basic statistics.
Distributed mode
The algorithm supports distributed execution in SPMD mode (only on GPU).
Usage Example
Computing
 void run_computing(const table& data) {
 const auto bs_desc = dal::basic_statistics::descriptor{};
 const auto result = dal::compute(bs_desc, data);
 std::cout << "Minimum:\n" << result.get_min() << std::endl;
 std::cout << "Maximum:\n" << result.get_max() << std::endl;
 std::cout << "Sum:\n" << result.get_sum() << std::endl;
 std::cout << "Sum of squares:\n" << result.get_sum_squares() << std::endl;
 std::cout << "Sum of squared difference from the means:\n"
     << result.get_sum_squares_centered() << std::endl;
 std::cout << "Mean:\n" << result.get_mean() << std::endl;
 std::cout << "Second order raw moment:\n" << result.get_second_order_raw_moment() << std::endl;
 std::cout << "Variance:\n" << result.get_variance() << std::endl;
 std::cout << "Standard deviation:\n" << result.get_standard_deviation() << std::endl;
 std::cout << "Variation:\n" << result.get_variation() << std::endl;
} 
  Examples
oneAPI DPC++
Batch Processing:
oneAPI C++
Batch Processing:









