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To answer your question no. The term "imbalance" usually refers to classification problems. For your case, i.e. a regression problem you can only look at the distribution of your target variable. If by "balance" you mean them having a uniform distribution, you could argue that they are, if fact imbalanced. However, I'd argue that this is not the problem ...


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You need to clean up the data. Load it into the Power Query editor. Split the column with the variables by the delimiter ; now you have a lot of individual columns, some have values, some are empty select all columns except the newly split ones and use Unpivot > Unpivot Other Columns on the transform ribbon. Now you have one row for each combination of ...


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With more than two variables, you have a dimension problem. Here, with 3 variables and one output you would need a 4 dimensionnal graph, which is not possible unless you use some trick. 1. Reduce the dimension of your problem Generally speaking, if you need to observe a problem for which the dimension is too big, you may want to reduce its dimension. ...


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If we limit the question on comparing two graphs, I can propose a way based on adjacency matrices comparison. There is a sample notebook: graph_diff.ipynb To summarize: Having two graphs, A B C D A B D E F A 0 2 2 2 A 0 1 2 3 0 B 2 0 1 1 B 1 0 0 1 1 C 2 1 2 0 D 2 ...


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