Supplementary Material: Model Class Reliance for Random Forests

Replication is facilitated through the provision of four hosted Python notebooks which replicate the paper results. When tested hosted runtimes were running Python 3.6.9 The packages developed as part of this work are discussed below and made available via the above notebooks. The code is written as an extension to the sklearn RandomForestRegressor and RandomForestClas-sifer classes. If running the notebooks on a hosted instance this will be automatically installed. The wrapper calls the R code from the lead author's github If running the notebooks on a hosted instance this will be automatically installed.