Update README.md

README.md

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 # Assessors For Regression: Loss Analysis - Instance Level Results
 
-AFRLA - Instance Level Results is a collection of predictions at the instance level for eleven different regression tasks tested on 255 tree-based models. The aim of this dataset is to provide example-level results to train assessor models to predict performance of the tree-based models.
+AFRLA - Instance Level Results is a collection of predictions at the instance/example level for eleven different regression tasks tested on 255 tree-based models (also called "base systems"). The aim of this dataset is to provide example-level results to train assessor models to predict performance of the tree-based models.
 
 ## The dataset
 
@@ -1206,6 +1206,8 @@ The dataset presents eleven sections (one per regression task), with varying deg
 
   These metrics are not recorded per example, but rather per model (that is, if the inference time is 1.2 ms, the model predicted *the entirety of the test dataset* in that time, instead of just that example), and are then casted for each example. As such, they fully describre a model.
 
+![Boo](./Nomenclature.png)
+
 ## Partitions and versions
 
 The sections are already partitioned into a predefined train-validation-test split for training assessors. Assessors need a particular kind of partitioning (mainly stratified by instance identifier to avoid contamination), so that's why the subsets are given.