# `Monty.Frameworks.Models.EvidenceMatching.BurstSampling`
[🔗](https://github.com/d-led/ex.tbp.monty/blob/v0.1.0/packages/ex_tbp_monty_core/lib/monty/frameworks/models/evidence_matching/burst_sampling.ex#L1)

Spending steps on new hypotheses when the current ones stop learning.

Mirrors `tbp/monty/frameworks/models/evidence_matching/burst_sampling.py`.

  * `Monty.Frameworks.Models.EvidenceMatching.BurstSampling.BurstSamplingHypothesesUpdater`
    — **ported**: the sampling strategy Monty's evidence matching runs, which
    keeps, drops or replaces hypotheses between steps;
  * `...BurstSampling.BurstSamplingTelemetry` — **ported**: what a step reports
    about the hypotheses it added, kept and removed.

`HypothesesUpdater` in the same family is the simpler strategy that only
accumulates evidence; this one is what experiments use.

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*Consult [api-reference.md](api-reference.md) for complete listing*