During the Data Insights stage, you select the target you want to predict, choose what machine learning method you want to use, review helpful information about correlations and outliers in the dataset, and view the distribution of data in the target.
Before you explore the information in the panels, choose the target you want to predict and the machine learning method you want to use.
You can also access Advanced settings at this stage.
Time series regression is an experimental feature. Experimental features offer early access to features. We test and update experimental features on a regular basis.
The Correlation Matrix and Chord Diagram show the strength of correlations between features in your dataset. Adjust the Correlation Threshold to filter out weak correlations from visualizations.
The Outliers panel shows what data points fall outside the expected distribution of your data. The box plots give you a high-level understanding of the distribution of data for each feature. Select a box plot to see a detailed distribution. Outliers are highlighted in red.
If a feature contains rows that are outliers, you can remove those rows from the dataset. Check the box associated with the rows you want to delete, then select Delete Selected Rows.
The Target panel shows the distribution of data in the target.