alteryx/evalml

Set drop NaN component in time series pipeline to be training-only

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#3,347 opened on Feb 18, 2022

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good first issue

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Description

Currently, we run the drop NaN component in time series pipelines during fit, transform, and predict. However, we only need to drop NaN values during training. When passing a test set though the pipeline, we shouldn't generate NaN values with the featurizer and thus do not need to have NaN rows to be dropped.

This has implications for calculating features for time series to be used for permutation importance.

Contributor guide

Research direction
Locate the drop NaN component in the time series pipeline and modify its behavior to only run during fit, not during transform or predict.
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.
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
Python
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
65