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The correlation does not effect your model using decision trees in a classification problem. In the theory of decision tree models, you don`t need correlation or check of multicollinearity. Because the split in decision trees is made of entropy/information gain. The correlation does only check linear dependencies. The same is, when the dataset is highly ...


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I believe boxplot or violin plot is a good idea and you could overlay datapoints with a bit of jitter to the former. See below an example in seaborn taken from a relevant question: import seaborn as sns import matplotlib.pyplot as plt tips = sns.load_dataset("tips") sns.violinplot(x="day", y="total_bill", data=tips, color=&...


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