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Visualisation and Outliers Removal via Weka
visualisation-and-outliers-removal-via-weka's Introduction
Visualisation-and-Outliers-Removal-via-Weka
Using the Visualize panel
- Open iris.arff
- Bring up Visualize panel
- Click one of the plots; examine some instances
- Set x axis to petalwidth and y axis to petallength
- Click on Class colour to change the colour
- Bars on the right change correspond to attributes: click for x axis;
right‐click for y axis
- Jitter slider
- Show Select Instance: Rectangle option
- Submit, Reset, Clear and Save
- Open diabetes data;
- Use the Visualize panel to select the outliers based on the feature "diabetes pedigree function".
- Find the InterquartileRange in the Filter;
- Read the detailed information;
- Apply InterquartileRange and report the outliers;
- Apply InterquartileRange and report the outliers only based on the feature "diabetes pedigree function".
- If we only need to output five outliers based on the feature "diabetes pedigree function", how?
- For this data, we identify the outliers with the values of the feature "diabetes pedigree function" >= 1.6. How to achieve this goal?
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