use bayesian model selection instead of heuristics for .guess

Description

This issue does not include a description.

Contributor guide

Tech stack

python

Domain

machine learning

Issue type

feature

DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.

4

Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.

over 1 week

Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.

stale

ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.

unclear

Prerequisites

Bayesian statisticsPythonbayeslite codebase

Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.

15

Research direction

The issue proposes replacing heuristic model selection with Bayesian model selection for the .guess method. First, locate the current heuristic implementation in the bayeslite source code (likely in Python). Then, research Bayesian model selection techniques such as Bayes factors or WAIC that can be applied. The implementation should modify the .guess method accordingly. Since the issue body is empty, the contributor should review any existing comments and the codebase structure to understand the current heuristic.