Visualising high dimensional data with Hiplot
Today I learnt about the parallel coordinates technique to visualise high dimensional data.
As demonstrated in this talk, Hiplot is a tool that allows you to visualise high dimensional tabular data. Not only is this useful for exploring a new data set, but it can help you manually find cuts in the data to create a sort of dumb decision tree - useful as a target to beat with a fancier machine learning model later in the project.
The speaker (Vincent Warmerdam), who is also the creator of the amazing calmcode project, demonstrates that such a tool can be used to evaluate the best hyperparameters in a grid search.
Try exploring how the house price in London varies with postcode, property type and number of bedrooms. Narrow down the range of each column, by dragging a box vertically, to see how the price changes (as represented by the colour and right most column)