KRLS

Package implements Kernel-based Regularized Least Squares (KRLS), a machine learning method to fit multidimensional functions y=f(x) for regression and classification problems without relying on linearity or additivity assumptions. KRLS finds the best fitting function by minimizing the squared loss of a Tikhonov regularization problem, using Gaussian kernels as radial basis functions. For further details see Hainmueller and Hazlett (2014).

Last 30 days

This package has been downloaded 292 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 7 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 3,696 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Sep 11, 2024 with 44 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.