Add a new sample to this summarizer, and update the statistical summary.
Add a new sample to this summarizer, and update the statistical summary.
The sample in dense/sparse vector format to be added into this summarizer.
This MultivariateOnlineSummarizer object.
Sample size.
Sample size.
Maximum value of each column.
Maximum value of each column.
Sample mean vector.
Sample mean vector.
Merge another MultivariateOnlineSummarizer, and update the statistical summary.
Merge another MultivariateOnlineSummarizer, and update the statistical summary.
(Note that it's in place merging; as a result, this object will be modified.)
The other MultivariateOnlineSummarizer to be merged.
This MultivariateOnlineSummarizer object.
Minimum value of each column.
Minimum value of each column.
L1 norm of each column
L1 norm of each column
Euclidean magnitude of each column
Euclidean magnitude of each column
Number of nonzero elements (including explicitly presented zero values) in each column.
Number of nonzero elements (including explicitly presented zero values) in each column.
Sample variance vector.
Sample variance vector. Should return a zero vector if the sample size is 1.
:: DeveloperApi :: MultivariateOnlineSummarizer implements MultivariateStatisticalSummary to compute the mean, variance, minimum, maximum, counts, and nonzero counts for samples in sparse or dense vector format in a online fashion.
Two MultivariateOnlineSummarizer can be merged together to have a statistical summary of the corresponding joint dataset.
A numerically stable algorithm is implemented to compute sample mean and variance: Reference: variance-wiki Zero elements (including explicit zero values) are skipped when calling add(), to have time complexity O(nnz) instead of O(n) for each column.