thesps/conifer

scikit-learn AdaBoostClassifier

Open

#9 opened on Nov 6, 2020

View on GitHub
 (1 comment) (0 reactions) (0 assignees)Python (32 forks)auto 404
enhancementgood first issue

Repository metrics

Stars
 (61 stars)
PR merge metrics
 (PR metrics pending)

Description

Currently, AdaBoost models from scikit-learn [1] are implicitly ignored by conifer's sklearn converter [2]. Neither of the existing BDT or RF converter methods work "out of the box" for AdaBoostClassifier, which names some attributes differently to the other methods. A new converter method will be needed. But since the base classifiers are DecisionTrees, it should not be a major addition.

[1] https://github.com/scikit-learn/scikit-learn/blob/0.21.3/sklearn/ensemble/weight_boosting.py#L292 [2] https://github.com/thesps/conifer/blob/master/conifer/converters/sklearn.py#L42-L46

Contributor guide

Research direction
Create a new converter method for scikit learn AdaBoostClassifier in conifer's sklearn converter, leveraging existing DecisionTree conversion logic.
Tech stack
pythonscikit learn
Domain
backendai
Issue type
Feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
2
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
1-3 hours
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
Active
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
Clear
Prerequisites
Pythonscikit learn
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
75