| Variance Optimal Sampling (VarOpt) |
| ---------------------------------- |
| |
| .. currentmodule:: datasketches |
| |
| A VarOpt sketch samples data from a stream of items. The sketch is desinged for optimal (minimum) |
| variance when querying the sketch to estimate subset sums of items matching a provided predicate. |
| The sketch will produce a sample of size `k` (or smaller if fewer items have been presented), with |
| the probability of including an item roughly corresponding it the item's weight relative to the total |
| weight of all items presented to the sketch. |
| |
| VarOpt sampling is related to reservoir sampling, with improved error bounds for subset sum estimation. |
| Feeding the sketch items with a uniform weight value will produce a sample equivalent to reservoir sampling. |
| |
| .. note:: |
| Serializing and deserializing this sketch requires the use of a :class:`PyObjectSerDe`. |
| |
| .. autoclass:: var_opt_sketch |
| :members: |
| :undoc-members: |
| :exclude-members: deserialize |
| |
| .. rubric:: Static Methods: |
| |
| .. automethod:: deserialize |
| |
| .. rubric:: Non-static Methods: |
| |
| .. automethod:: __init__ |
| |
| .. autoclass:: var_opt_union |
| :members: |
| :undoc-members: |
| :exclude-members: deserialize |
| |
| .. rubric:: Static Methods: |
| |
| .. automethod:: deserialize |
| |
| .. rubric:: Non-static Methods: |
| |
| .. automethod:: __init__ |
