Use HF-compatible task name

README.md

@@ -1,5 +1,5 @@
 ---
-pretty_name: SRSD-Feynman (Easy w/ Dummy Variables)
+pretty_name: SRSD-Feynman (Medium w/ Dummy Variables)
 annotations_creators:
 - expert
 language_creators:
@@ -15,11 +15,11 @@ size_categories:
 source_datasets:
 - extended
 task_categories:
-- symbolic-regression
+- tabular-regression
 task_ids: []
 ---
 
-# Dataset Card for SRSD-Feynman (Easy set with Dummy Variables)
+# Dataset Card for SRSD-Feynman (Medium set with Dummy Variables)
 
 ## Table of Contents
 - [Table of Contents](#table-of-contents)
@@ -58,18 +58,18 @@ task_ids: []
 Our SRSD (Feynman) datasets are designed to discuss the performance of Symbolic Regression for Scientific Discovery.
 We carefully reviewed the properties of each formula and its variables in [the Feynman Symbolic Regression Database](https://space.mit.edu/home/tegmark/aifeynman.html) to design reasonably realistic sampling range of values so that our SRSD datasets can be used for evaluating the potential of SRSD such as whether or not an SR method con (re)discover physical laws from such datasets.
 
-This is the ***Easy set with dummy variables*** of our SRSD-Feynman datasets, which consists of the following 30 different physics formulas:
+This is the ***Medium set with dummy variables*** of our SRSD-Feynman datasets, which consists of the following 40 different physics formulas:
 
-[![Click here to open a PDF file](problem_table.png)](https://huggingface.co/datasets/yoshitomo-matsubara/srsd-feynman_easy_dummy/resolve/main/problem_table.pdf)
+[![Click here to open a PDF file](problem_table.png)](https://huggingface.co/datasets/yoshitomo-matsubara/srsd-feynman_medium_dummy/resolve/main/problem_table.pdf)
   
 Dummy variables were randomly generated, and symbolic regression models should not use the dummy variables as part of their predictions.
 
 The following datasets contain  
-**1 dummy variable**: I.12.1, I.12.4, I.12.5, I.18.12, I.25.13, I.47.23
+**1 dummy variable**: I.10.7, I.12.2, I.13.12, I.16.6, I.32.5, I.43.31, II.11.3, II.34.2, II.34.29a, III.14.14, III.15.14, B8
 
-**2 dummy variables**: I.14.3, I.18.16, I.43.16, II.3.24, II.8.31, II.10.9, II.13.17, II.15.5, II.27.18, III.7.38, III.12.43
+**2 dummy variables**: I.11.19, I.12.11, I.13.4, I.15.10, I.18.4, I.24.6, I.34.8, I.38.12, I.39.11, I.43.43, I.48.2, II.6.11, II.21.32, II.34.2a, III.4.32, III.13.18, III.15.12, III.17.37
 
-**3 dummy variables**: I.14.4, I.26.2, I.27.6, I.30.5, II.2.42, II.4.23, II.15.4, II.27.16, II.34.11, II.34.29b, II.38.3, II.38.14, III.15.27
+**3 dummy variables**: I.8.14, I.29.4, I.34.10, I.34.27, I.39.10, II.8.7, II.37.1, III.8.54, III.19.51, B18
 
 More details of these datasets are provided in [the paper and its supplementary material](https://arxiv.org/abs/2206.10540).