bcgov / bcgov/wps

FOP: Build models using new features

Open
#2,092 0 comments 0 reactions 0 assignees View on GitHub
Task
Dominant language
Python
Stars
65
Forks
11
Avg merge
21h 25m
Merged PRs (30d)
70

Description

**Describe the task**
Build, train, and evaluate models using new features.

**Acceptance Criteria**
- [ ] Understand what features are useful for fire occurrence prediction in BC.
- [ ] Quantify the accuracy of predictions.
- [ ] Explore if there are different geospatial contexts for training FOP models throughout the province.

**Additional context**
- Add any other context about the task here.
- Or here

Contributor guide

Open the contributing guide

Research direction

The issue names no files, tests, or entry points. Start by locating the existing fire occurrence prediction model and its training and evaluation data, then determine which features and geographic contexts are available. Done means documenting useful features, quantified prediction accuracy, and any province-wide geospatial differences in model training.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
data, machine-learning
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
20/100

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.