Add transductive experiment yaml instead of triangle counting task

Author: LouisVanLangendonck

…figs/dataset/graph/GraphUniverse_TC.yaml …et/graph/graphuniverse_transductive.yamlconfigs/dataset/graph/GraphUniverse_TC.yaml renamed to configs/dataset/graph/graphuniverse_transductive.yaml configs/dataset/graph/GraphUniverse_TC.yaml renamed to configs/dataset/graph/graphuniverse_transductive.yaml

@@ -7,37 +7,37 @@ loader:
     data_name: GraphUniverse
     data_dir: ${paths.data_dir}/${dataset.loader.parameters.data_domain}/${dataset.loader.parameters.data_type}
     generation_parameters:
-      task: triangle_counting
+      task: community_detection
       universe_parameters:
-        K: 20
+        K: 10
         feature_dim: 15
         center_variance: 0.2
-        cluster_variance: 0.4
-        edge_propensity_variance: 1.0
+        cluster_variance: 0.5
+        edge_propensity_variance: 0.5
         seed: 42
       family_parameters:
-        n_graphs: 1000
-        n_nodes_range: [50, 200]
-        n_communities_range: [3, 7]
-        homophily_range: [0.4, 0.8]
-        avg_degree_range: [1.0, 2.0]
-        degree_separation_range: [0.5, 1.0]
-        power_law_exponent_range: [1.5, 2.5]
+        n_graphs: 1
+        n_nodes_range: [5000, 5000]
+        n_communities_range: [10, 10]
+        homophily_range: [0.5, 0.5]
+        avg_degree_range: [2.5, 2.5]
+        degree_separation_range: [0.5, 0.5]
+        power_law_exponent_range: [2.5, 2.5]
         seed: ${dataset.loader.parameters.generation_parameters.universe_parameters.seed}
 
 
 # Dataset parameters
 parameters:
   num_features: ${dataset.loader.parameters.generation_parameters.universe_parameters.feature_dim}
-  num_classes: 1
-  task: regression
-  loss_type: mae
-  monitor_metric: mae
-  task_level: graph
+  num_classes: ${dataset.loader.parameters.generation_parameters.universe_parameters.K}
+  task: classification
+  loss_type: cross_entropy
+  monitor_metric: accuracy
+  task_level: node
 
 #splits
 split_params:
-  learning_setting: inductive
+  learning_setting: transductive
   data_split_dir: ${dataset.loader.parameters.data_dir}/data_splits
   data_seed: 0
   split_type: random #'k-fold' # either "k-fold" or "random" strategies
@@ -46,6 +46,6 @@ split_params:
 
 # Dataloader parameters
 dataloader_params:
-  batch_size: 16 
+  batch_size: 1
   num_workers: 0
   pin_memory: False