ExplainPrediction

Generates explanations for classification and regression models and visualizes them. Explanations are generated for individual predictions as well as for models as a whole. Two explanation methods are included, EXPLAIN and IME. The EXPLAIN method is fast but might miss explanations expressed redundantly in the model. The IME method is slower as it samples from all feature subsets. For the EXPLAIN method see Robnik-Sikonja and Kononenko (2008) doi:10.1109/TKDE.2007.190734, and the IME method is described in Strumbelj and Kononenko (2010, JMLR, vol. 11:1-18). All models in package 'CORElearn' are natively supported, for other prediction models a wrapper function is provided and illustrated for models from packages 'randomForest', 'nnet', and 'e1071'.

Last 30 days

This package has been downloaded 258 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 3 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 3,124 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 Jul 21, 2024 with 132 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.