Multiclass Classification of Dry Beans
Multiclass Classification of Dry Beans
About Makeover Monday
MakeoverMonday is a social data project: “Each week we post a link to a chart, and its data, and then you rework the chart. Maybe you retell the story more effectively, or find a new story in the data. We’re curious to see the different approaches you all take. Whether it’s a simple bar chart or an elaborate infographic, we encourage everyone of all skills to partake. Together we can have broader conversations about and with data.”
Starting from Jan 08, 2018, I decided to put aside one hour on Monday weekly to create some visualization and find some insights from the data.
The datasets are published each week at: MakeoverMonday Datasets.
Makeover Monday 20210405
This week we are looking at a public dataset from UCI Machine Learning Repository – the Dry Bean dataset. It collects multiple attributes regarding dry beans, like area, compactness, major axis length, etcs, and their classes. Its a very useful dataset for beginners to practice multiclass classification.
My Visualization
I created a viz for the purpose of EDA – you can pick four measures and look at their univariate distribution and 2x2 intersections by bean classes.
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Please notice that all the visualizations are designed for desktop view, so it is recommended to view them on a desktop device.
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Insights
- Bombay seems like a easy to classify bean as its has much larger area compared to the others;
- We can clearly see some correlation between feature pairs, for example, compactness and aspect ratio are negatively correlated.
Follow this link to find more weekly vizzes :)
