visualize classifier prediction, scatter
I would like to plot a scatter plot like this, where you can see the wrong predicted and true predicitons of a classifier including the numbers of the predicitons
i tried with this scatter plot till now
predictions_rf = rf.predict(X_test)
plt.figure(figsize=(10,10))
plt.gca().set_aspect('equal', adjustable='box')
plt.scatter(Y_test,predictions_rf)
plt.xlabel("True Values")
plt.ylabel("Predictions")
and i got a scatter plot like this:
It is possible to see the wrong estimated ones as well but not diagonally and not with the numbers the model predicted right and wrong
How could I improve my code to get a solution like the first one?
Thank you
python matplotlib classification scatter
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I would like to plot a scatter plot like this, where you can see the wrong predicted and true predicitons of a classifier including the numbers of the predicitons
i tried with this scatter plot till now
predictions_rf = rf.predict(X_test)
plt.figure(figsize=(10,10))
plt.gca().set_aspect('equal', adjustable='box')
plt.scatter(Y_test,predictions_rf)
plt.xlabel("True Values")
plt.ylabel("Predictions")
and i got a scatter plot like this:
It is possible to see the wrong estimated ones as well but not diagonally and not with the numbers the model predicted right and wrong
How could I improve my code to get a solution like the first one?
Thank you
python matplotlib classification scatter
add a comment |
I would like to plot a scatter plot like this, where you can see the wrong predicted and true predicitons of a classifier including the numbers of the predicitons
i tried with this scatter plot till now
predictions_rf = rf.predict(X_test)
plt.figure(figsize=(10,10))
plt.gca().set_aspect('equal', adjustable='box')
plt.scatter(Y_test,predictions_rf)
plt.xlabel("True Values")
plt.ylabel("Predictions")
and i got a scatter plot like this:
It is possible to see the wrong estimated ones as well but not diagonally and not with the numbers the model predicted right and wrong
How could I improve my code to get a solution like the first one?
Thank you
python matplotlib classification scatter
I would like to plot a scatter plot like this, where you can see the wrong predicted and true predicitons of a classifier including the numbers of the predicitons
i tried with this scatter plot till now
predictions_rf = rf.predict(X_test)
plt.figure(figsize=(10,10))
plt.gca().set_aspect('equal', adjustable='box')
plt.scatter(Y_test,predictions_rf)
plt.xlabel("True Values")
plt.ylabel("Predictions")
and i got a scatter plot like this:
It is possible to see the wrong estimated ones as well but not diagonally and not with the numbers the model predicted right and wrong
How could I improve my code to get a solution like the first one?
Thank you
python matplotlib classification scatter
python matplotlib classification scatter
edited Nov 14 '18 at 14:49
Tadej Magajna
1,1201332
1,1201332
asked Nov 14 '18 at 14:37
raffa_saraffa_sa
1257
1257
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add a comment |
1 Answer
1
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oldest
votes
What you are trying to plot is a confusion matrix.
Sklearn's confusion matrix described here does exactly what you're looking for.
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
What you are trying to plot is a confusion matrix.
Sklearn's confusion matrix described here does exactly what you're looking for.
add a comment |
What you are trying to plot is a confusion matrix.
Sklearn's confusion matrix described here does exactly what you're looking for.
add a comment |
What you are trying to plot is a confusion matrix.
Sklearn's confusion matrix described here does exactly what you're looking for.
What you are trying to plot is a confusion matrix.
Sklearn's confusion matrix described here does exactly what you're looking for.
answered Nov 14 '18 at 14:42
Tadej MagajnaTadej Magajna
1,1201332
1,1201332
add a comment |
add a comment |
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