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UBC-MDS / abalone_age_classification

In this project, we are classifying abalone snails into "young" and "old" according to their number of rings based on input features such as abalone's gender, height with meat in shell, the weight of the shell, etc.
https://ubc-mds.github.io/abalone_age_classification/
MIT License
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Reasoning for EDA literate document requires revision #72

Closed kphaterp closed 2 years ago

kphaterp commented 2 years ago

How does the unbalanced target variables influence your interpretation of EDA and potentially your results?

You have a lot of EDA results, which ones are effective in guiding you to address future steps in the project. Does it affect your hypothesis of the results from your task?

Feature variables are highly correlated, and what does that imply? Are there potentially lurking or redundant variables?

nickmao1994 commented 2 years ago

Nick - deal with item three: Feature variables are highly correlated and one other issue why logistic regression is chosen.

kphaterp commented 2 years ago

Kiran - item 1: How does the unbalanced target variables influence your interpretation of EDA and potentially your results?