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I have a neural network that predicts frequencies for four different features in my dataset. I then test my network and therefore for each input I get a vector of size four where each entry corresponds to frequency of a given feature. Now I want to plot a 2D density plot of true frequencies vs predicted frequencies.


true: [0.000345,0.99183,0,0] prediction: [0.0212,0.738,0.004,0.006]
true: [0,0.9937,0,0.00013]   prediction: [0.005,0.983,0.04,0.01]

I basically plot 2D density plot for each of the features separately. That is I would plot true vs predictions for feature # 1, then for feature # 2 and so on.

import seaborn as sns
sns.jointplot(x=feature_1_true, y=feature_1_pred, kind='scatter')
sns.jointplot(x=feature_2_true, y=feature_2_pred, kind='scatter')

My question is there a way to visualise such a vector in totality on a density plot instead of plotting features separately. If you had a vector of such kind how would you plot it's density plot and how would you plot true vs predictions.

John
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  • This should answer your question [How to plot a density map in python?](https://stackoverflow.com/questions/24119920/how-to-plot-a-density-map-in-python) – itprorh66 Jan 14 '21 at 21:48
  • Does this answer your question? [How to plot a density map in python?](https://stackoverflow.com/questions/24119920/how-to-plot-a-density-map-in-python) – itprorh66 Jan 14 '21 at 21:48
  • No. I came across this post too. But It's not what I want to do. Thanks anyway :) – John Jan 15 '21 at 10:59

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