Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
machine-learning
sklearn
community-detection
network-science
deepwalk
networkx
supervised-learning
louvain
unsupervised-learning
network-embedding
scikit
label-propagation
gcn
graph-clustering
node2vec
networkx-graph
graph-embedding
graph2vec
node-embedding
2vec
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Updated
Jan 22, 2022 - Python
Hello, I have a CSV file that has 9 features and 9 expected targets, and I want to test 2 regression models on this data (that should be generated as a stream).
When I test the
MultiTargetRegressionHoeffdingTreeandRegressorChainon this data I get a bad R2-score, but when I tried normalizing my data with scikit-learn I get a pretty good R2-score. The problem is that I should not use sci