iiitl / iiitl/Decision-Tree

Handle missing values and check target class balance

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#10 44 comments 0 reactions 0 assignees View on GitHub
good first issue track: exploration very easy
Dominant language
Jupyter Notebook
Stars
0
Forks
16
PR merge metrics
No merged PRs in 30d

Description

Analyze the dataset for missing values and check the distribution of the income target variable. Write 3 to 4 points on how the missing data should be handled and the potential impact of the class distribution on tree splitting.

Contributor guide

Open the contributing guide

Research direction

Start by locating the dataset and notebook entry point, then inspect missing values and the distribution of the income target variable. Document 3 to 4 points covering missing-data handling and how class distribution may affect tree splitting; done means the analysis and recommendations are written in the notebook or project documentation.

Written by the indexing model from the issue text.

Assessment

Tech stack
jupyter-notebook
Domain
data, machine-learning
Issue type
Documentation
Difficulty
2/5
Estimated time
Half a day
Activity status
Quiet
Clarity
Mostly clear
Newbie friendliness
48/100

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