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I want to print a heatmap of a confusion matrix based on my results of y_predict and y_train.
I'm a bit stuck and I already looked up the pandas documentation of the heatmap, but still don't know how to apply it on my results. The dataset I used is about incomes and has categorical and numerical data. I've already applied the GB classifier and I got an result.
The only thing that remains is the heatmap.
print(confusion_matrix(y_train,y_pred_train))
print(y_train)
this was the outcome
Confusion Matrix:
[[14151 710]
[ 1844 2831]]
Name: income, Length: 19536, dtype: int64
this was an attempt to make a heatmap
import seaborn as sns
class_names = y_train, y_pred_train
def print_confusion_matrix(confusion_matrix, class_names, figsize = (10,7), fontsize=14):
df_cm = pd.DataFrame(
confusion_matrix, index=class_names, columns=class_names,
)
fig = plt.figure(figsize=figsize)
try:
heatmap = sns.heatmap(df_cm, annot=True, fmt="d")
except ValueError:
raise ValueError("Confusion matrix values must be integers.")
heatmap.yaxis.set_ticklabels(heatmap.yaxis.get_ticklabels(), rotation=0, ha='right', fontsize=fontsize)
heatmap.xaxis.set_ticklabels(heatmap.xaxis.get_ticklabels(), rotation=45, ha='right', fontsize=fontsize)
plt.ylabel('True label')
plt.xlabel('Predicted label')
return fig
which returned
NameError Traceback (most recent call last)
<ipython-input-36-3bd0e9ee90a4> in <module>()
18 plt.xlabel('Predicted label')
19 return fig
---> 20 print(fig)
NameError: name 'fig' is not defined
So what am I missing when I'm making the heatmap of the confusion matrix on my results?
python pandas machine-learning seaborn
edited Mar 28 at 0:13
Brian
9458 silver badges19 bronze badges
asked Mar 27 at 19:16
b34tsb34ts
11 bronze badge
add a comment |
I want to print a heatmap of a confusion matrix based on my results of y_predict and y_train.
I'm a bit stuck and I already looked up the pandas documentation of the heatmap, but still don't know how to apply it on my results. The dataset I used is about incomes and has categorical and numerical data. I've already applied the GB classifier and I got an result.
The only thing that remains is the heatmap.
print(confusion_matrix(y_train,y_pred_train))
print(y_train)
this was the outcome
Confusion Matrix:
[[14151 710]
[ 1844 2831]]
Name: income, Length: 19536, dtype: int64
this was an attempt to make a heatmap
import seaborn as sns
class_names = y_train, y_pred_train
def print_confusion_matrix(confusion_matrix, class_names, figsize = (10,7), fontsize=14):
df_cm = pd.DataFrame(
confusion_matrix, index=class_names, columns=class_names,
)
fig = plt.figure(figsize=figsize)
try:
heatmap = sns.heatmap(df_cm, annot=True, fmt="d")
except ValueError:
raise ValueError("Confusion matrix values must be integers.")
heatmap.yaxis.set_ticklabels(heatmap.yaxis.get_ticklabels(), rotation=0, ha='right', fontsize=fontsize)
heatmap.xaxis.set_ticklabels(heatmap.xaxis.get_ticklabels(), rotation=45, ha='right', fontsize=fontsize)
plt.ylabel('True label')
plt.xlabel('Predicted label')
return fig
which returned
NameError Traceback (most recent call last)
<ipython-input-36-3bd0e9ee90a4> in <module>()
18 plt.xlabel('Predicted label')
19 return fig
---> 20 print(fig)
NameError: name 'fig' is not defined
So what am I missing when I'm making the heatmap of the confusion matrix on my results?
python pandas machine-learning seaborn
edited Mar 28 at 0:13
Brian
9458 silver badges19 bronze badges
asked Mar 27 at 19:16
b34tsb34ts
11 bronze badge
You can call the function with your confusion matrix, see my answer for an example
– perl
Mar 27 at 19:52
And the error onprint(fig)is thatfigis defined inside the function, and if you want to use it outside the scope of the function, you can set it withfig = print_confusion_matrix(...since it's returned from your function withreturn fig
– perl
Mar 27 at 20:00
add a comment |
I want to print a heatmap of a confusion matrix based on my results of y_predict and y_train.
I'm a bit stuck and I already looked up the pandas documentation of the heatmap, but still don't know how to apply it on my results. The dataset I used is about incomes and has categorical and numerical data. I've already applied the GB classifier and I got an result.
The only thing that remains is the heatmap.
print(confusion_matrix(y_train,y_pred_train))
print(y_train)
this was the outcome
Confusion Matrix:
[[14151 710]
[ 1844 2831]]
Name: income, Length: 19536, dtype: int64
this was an attempt to make a heatmap
import seaborn as sns
class_names = y_train, y_pred_train
def print_confusion_matrix(confusion_matrix, class_names, figsize = (10,7), fontsize=14):
df_cm = pd.DataFrame(
confusion_matrix, index=class_names, columns=class_names,
)
fig = plt.figure(figsize=figsize)
try:
heatmap = sns.heatmap(df_cm, annot=True, fmt="d")
except ValueError:
raise ValueError("Confusion matrix values must be integers.")
heatmap.yaxis.set_ticklabels(heatmap.yaxis.get_ticklabels(), rotation=0, ha='right', fontsize=fontsize)
heatmap.xaxis.set_ticklabels(heatmap.xaxis.get_ticklabels(), rotation=45, ha='right', fontsize=fontsize)
plt.ylabel('True label')
plt.xlabel('Predicted label')
return fig
which returned
NameError Traceback (most recent call last)
<ipython-input-36-3bd0e9ee90a4> in <module>()
18 plt.xlabel('Predicted label')
19 return fig
---> 20 print(fig)
NameError: name 'fig' is not defined
So what am I missing when I'm making the heatmap of the confusion matrix on my results?
python pandas machine-learning seaborn
edited Mar 28 at 0:13
Brian
9458 silver badges19 bronze badges
asked Mar 27 at 19:16
b34tsb34ts
11 bronze badge
I want to print a heatmap of a confusion matrix based on my results of y_predict and y_train.
I'm a bit stuck and I already looked up the pandas documentation of the heatmap, but still don't know how to apply it on my results. The dataset I used is about incomes and has categorical and numerical data. I've already applied the GB classifier and I got an result.
The only thing that remains is the heatmap.
print(confusion_matrix(y_train,y_pred_train))
print(y_train)
this was the outcome
Confusion Matrix:
[[14151 710]
[ 1844 2831]]
Name: income, Length: 19536, dtype: int64
this was an attempt to make a heatmap
import seaborn as sns
class_names = y_train, y_pred_train
def print_confusion_matrix(confusion_matrix, class_names, figsize = (10,7), fontsize=14):
df_cm = pd.DataFrame(
confusion_matrix, index=class_names, columns=class_names,
)
fig = plt.figure(figsize=figsize)
try:
heatmap = sns.heatmap(df_cm, annot=True, fmt="d")
except ValueError:
raise ValueError("Confusion matrix values must be integers.")
heatmap.yaxis.set_ticklabels(heatmap.yaxis.get_ticklabels(), rotation=0, ha='right', fontsize=fontsize)
heatmap.xaxis.set_ticklabels(heatmap.xaxis.get_ticklabels(), rotation=45, ha='right', fontsize=fontsize)
plt.ylabel('True label')
plt.xlabel('Predicted label')
return fig
which returned
NameError Traceback (most recent call last)
<ipython-input-36-3bd0e9ee90a4> in <module>()
18 plt.xlabel('Predicted label')
19 return fig
---> 20 print(fig)
NameError: name 'fig' is not defined
So what am I missing when I'm making the heatmap of the confusion matrix on my results?
python pandas machine-learning seaborn
python pandas machine-learning seaborn
edited Mar 28 at 0:13
Brian
9458 silver badges19 bronze badges
asked Mar 27 at 19:16
b34tsb34ts
11 bronze badge
edited Mar 28 at 0:13
Brian
9458 silver badges19 bronze badges
asked Mar 27 at 19:16
b34tsb34ts
11 bronze badge
edited Mar 28 at 0:13
Brian
9458 silver badges19 bronze badges
edited Mar 28 at 0:13
Brian
9458 silver badges19 bronze badges
edited Mar 28 at 0:13
Brian
9458 silver badges19 bronze badges
9458 silver badges19 bronze badges
asked Mar 27 at 19:16
b34tsb34ts
11 bronze badge
asked Mar 27 at 19:16
b34tsb34ts
11 bronze badge
asked Mar 27 at 19:16
b34tsb34ts
11 bronze badge
11 bronze badge
You can call the function with your confusion matrix, see my answer for an example
– perl
Mar 27 at 19:52
And the error onprint(fig)is thatfigis defined inside the function, and if you want to use it outside the scope of the function, you can set it withfig = print_confusion_matrix(...since it's returned from your function withreturn fig
– perl
Mar 27 at 20:00
add a comment |
You can call the function with your confusion matrix, see my answer for an example
– perl
Mar 27 at 19:52
And the error onprint(fig)is thatfigis defined inside the function, and if you want to use it outside the scope of the function, you can set it withfig = print_confusion_matrix(...since it's returned from your function withreturn fig
– perl
Mar 27 at 20:00
You can call the function with your confusion matrix, see my answer for an example
– perl
Mar 27 at 19:52
You can call the function with your confusion matrix, see my answer for an example
– perl
Mar 27 at 19:52
And the error on
print(fig) is that fig is defined inside the function, and if you want to use it outside the scope of the function, you can set it with fig = print_confusion_matrix(... since it's returned from your function with return fig– perl
Mar 27 at 20:00
And the error on
print(fig) is that fig is defined inside the function, and if you want to use it outside the scope of the function, you can set it with fig = print_confusion_matrix(... since it's returned from your function with return fig– perl
Mar 27 at 20:00
add a comment |
1 Answer
1
active
oldest
votes
You can call your print_confusion_matrix function with the confusion matrix and class names list as parameters:
def print_confusion_matrix(confusion_matrix, class_names, figsize = (10,7), fontsize=14):
df_cm = pd.DataFrame(
confusion_matrix, index=class_names, columns=class_names,
)
fig = plt.figure(figsize=figsize)
try:
heatmap = sns.heatmap(df_cm, annot=True, fmt="d")
except ValueError:
raise ValueError("Confusion matrix values must be integers.")
heatmap.yaxis.set_ticklabels(heatmap.yaxis.get_ticklabels(), rotation=0, ha='right', fontsize=fontsize)
heatmap.xaxis.set_ticklabels(heatmap.xaxis.get_ticklabels(), rotation=45, ha='right', fontsize=fontsize)
plt.ylabel('True label')
plt.xlabel('Predicted label')
return fig
confusion_matrix = np.array([[14151, 710], [1844, 2831]])
fig = print_confusion_matrix(confusion_matrix, ['0', '1'])
Output:
answered Mar 27 at 19:52
perlperl
2,1014 silver badges17 bronze badges
1
Thank you very much for your help!
– b34ts
Mar 27 at 20:55
add a comment |
Your Answer
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You can call your print_confusion_matrix function with the confusion matrix and class names list as parameters:
def print_confusion_matrix(confusion_matrix, class_names, figsize = (10,7), fontsize=14):
df_cm = pd.DataFrame(
confusion_matrix, index=class_names, columns=class_names,
)
fig = plt.figure(figsize=figsize)
try:
heatmap = sns.heatmap(df_cm, annot=True, fmt="d")
except ValueError:
raise ValueError("Confusion matrix values must be integers.")
heatmap.yaxis.set_ticklabels(heatmap.yaxis.get_ticklabels(), rotation=0, ha='right', fontsize=fontsize)
heatmap.xaxis.set_ticklabels(heatmap.xaxis.get_ticklabels(), rotation=45, ha='right', fontsize=fontsize)
plt.ylabel('True label')
plt.xlabel('Predicted label')
return fig
confusion_matrix = np.array([[14151, 710], [1844, 2831]])
fig = print_confusion_matrix(confusion_matrix, ['0', '1'])
Output:
answered Mar 27 at 19:52
perlperl
2,1014 silver badges17 bronze badges
1
Thank you very much for your help!
– b34ts
Mar 27 at 20:55
add a comment |
You can call your print_confusion_matrix function with the confusion matrix and class names list as parameters:
def print_confusion_matrix(confusion_matrix, class_names, figsize = (10,7), fontsize=14):
df_cm = pd.DataFrame(
confusion_matrix, index=class_names, columns=class_names,
)
fig = plt.figure(figsize=figsize)
try:
heatmap = sns.heatmap(df_cm, annot=True, fmt="d")
except ValueError:
raise ValueError("Confusion matrix values must be integers.")
heatmap.yaxis.set_ticklabels(heatmap.yaxis.get_ticklabels(), rotation=0, ha='right', fontsize=fontsize)
heatmap.xaxis.set_ticklabels(heatmap.xaxis.get_ticklabels(), rotation=45, ha='right', fontsize=fontsize)
plt.ylabel('True label')
plt.xlabel('Predicted label')
return fig
confusion_matrix = np.array([[14151, 710], [1844, 2831]])
fig = print_confusion_matrix(confusion_matrix, ['0', '1'])
Output:
answered Mar 27 at 19:52
perlperl
2,1014 silver badges17 bronze badges
1
Thank you very much for your help!
– b34ts
Mar 27 at 20:55
add a comment |
You can call your print_confusion_matrix function with the confusion matrix and class names list as parameters:
def print_confusion_matrix(confusion_matrix, class_names, figsize = (10,7), fontsize=14):
df_cm = pd.DataFrame(
confusion_matrix, index=class_names, columns=class_names,
)
fig = plt.figure(figsize=figsize)
try:
heatmap = sns.heatmap(df_cm, annot=True, fmt="d")
except ValueError:
raise ValueError("Confusion matrix values must be integers.")
heatmap.yaxis.set_ticklabels(heatmap.yaxis.get_ticklabels(), rotation=0, ha='right', fontsize=fontsize)
heatmap.xaxis.set_ticklabels(heatmap.xaxis.get_ticklabels(), rotation=45, ha='right', fontsize=fontsize)
plt.ylabel('True label')
plt.xlabel('Predicted label')
return fig
confusion_matrix = np.array([[14151, 710], [1844, 2831]])
fig = print_confusion_matrix(confusion_matrix, ['0', '1'])
Output:
answered Mar 27 at 19:52
perlperl
2,1014 silver badges17 bronze badges
You can call your print_confusion_matrix function with the confusion matrix and class names list as parameters:
def print_confusion_matrix(confusion_matrix, class_names, figsize = (10,7), fontsize=14):
df_cm = pd.DataFrame(
confusion_matrix, index=class_names, columns=class_names,
)
fig = plt.figure(figsize=figsize)
try:
heatmap = sns.heatmap(df_cm, annot=True, fmt="d")
except ValueError:
raise ValueError("Confusion matrix values must be integers.")
heatmap.yaxis.set_ticklabels(heatmap.yaxis.get_ticklabels(), rotation=0, ha='right', fontsize=fontsize)
heatmap.xaxis.set_ticklabels(heatmap.xaxis.get_ticklabels(), rotation=45, ha='right', fontsize=fontsize)
plt.ylabel('True label')
plt.xlabel('Predicted label')
return fig
confusion_matrix = np.array([[14151, 710], [1844, 2831]])
fig = print_confusion_matrix(confusion_matrix, ['0', '1'])
Output:
answered Mar 27 at 19:52
perlperl
2,1014 silver badges17 bronze badges
answered Mar 27 at 19:52
perlperl
2,1014 silver badges17 bronze badges
answered Mar 27 at 19:52
perlperl
2,1014 silver badges17 bronze badges
answered Mar 27 at 19:52
perlperl
2,1014 silver badges17 bronze badges
2,1014 silver badges17 bronze badges
1
Thank you very much for your help!
– b34ts
Mar 27 at 20:55
add a comment |
1
Thank you very much for your help!
– b34ts
Mar 27 at 20:55
1
1
Thank you very much for your help!
– b34ts
Mar 27 at 20:55
Thank you very much for your help!
– b34ts
Mar 27 at 20:55
add a comment |
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You can call the function with your confusion matrix, see my answer for an example
– perl
Mar 27 at 19:52
And the error on
print(fig)is thatfigis defined inside the function, and if you want to use it outside the scope of the function, you can set it withfig = print_confusion_matrix(...since it's returned from your function withreturn fig– perl
Mar 27 at 20:00