is it possible determine a best neural network classifier by considering only accuracy The 2019 Stack Overflow Developer Survey Results Are InDebugging Neural Network for (Natural Language) TaggingNLTK: Tuning LinearSVC classifier accuracy? - Looking for better approaches/advicesQuery regarding neural network modelNetwork design for extracting MFCC features from audio samplesDeep Neural Network using Keras/Tensorflow solves Spiral Dataset Classification. But Accuracy is stuck around 50%Neural network accuracy for simple classificationHow to improve accuracy of deep neural networksNeural Network unable to track training dataDeep Learning Network decreasing in accuracyAccuracy keep changing by changing randomState of classifier
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is it possible determine a best neural network classifier by considering only accuracy
The 2019 Stack Overflow Developer Survey Results Are InDebugging Neural Network for (Natural Language) TaggingNLTK: Tuning LinearSVC classifier accuracy? - Looking for better approaches/advicesQuery regarding neural network modelNetwork design for extracting MFCC features from audio samplesDeep Neural Network using Keras/Tensorflow solves Spiral Dataset Classification. But Accuracy is stuck around 50%Neural network accuracy for simple classificationHow to improve accuracy of deep neural networksNeural Network unable to track training dataDeep Learning Network decreasing in accuracyAccuracy keep changing by changing randomState of classifier
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Below, you have the accuracy plots for training and testing set for 6 different neural networks. is it possible to say, which of the following neural network classifier is better?. Having this little known information (training and testing accuracy by number of epochs plot) ? . Personally, I believe, the first classifier (top-left corner) is better because it shows that the accuracy of the testing data is stable as the number of epochs increases.
machine-learning neural-network deep-learning
asked 5 hours ago
zeelloszeellos
61
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zeellos is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
$begingroup$
Below, you have the accuracy plots for training and testing set for 6 different neural networks. is it possible to say, which of the following neural network classifier is better?. Having this little known information (training and testing accuracy by number of epochs plot) ? . Personally, I believe, the first classifier (top-left corner) is better because it shows that the accuracy of the testing data is stable as the number of epochs increases.
machine-learning neural-network deep-learning
asked 5 hours ago
zeelloszeellos
61
New contributor
zeellos is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
$begingroup$
Your plots are slightly different in scale, consider using a fixed range for y-axis (plt.ylim([80,100]) or [0,100] would be best
$endgroup$
– Pedro Henrique Monforte
2 hours ago
add a comment |
$begingroup$
Below, you have the accuracy plots for training and testing set for 6 different neural networks. is it possible to say, which of the following neural network classifier is better?. Having this little known information (training and testing accuracy by number of epochs plot) ? . Personally, I believe, the first classifier (top-left corner) is better because it shows that the accuracy of the testing data is stable as the number of epochs increases.
machine-learning neural-network deep-learning
asked 5 hours ago
zeelloszeellos
61
New contributor
zeellos is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
Below, you have the accuracy plots for training and testing set for 6 different neural networks. is it possible to say, which of the following neural network classifier is better?. Having this little known information (training and testing accuracy by number of epochs plot) ? . Personally, I believe, the first classifier (top-left corner) is better because it shows that the accuracy of the testing data is stable as the number of epochs increases.
machine-learning neural-network deep-learning
machine-learning neural-network deep-learning
asked 5 hours ago
zeelloszeellos
61
New contributor
zeellos is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 5 hours ago
zeelloszeellos
61
New contributor
zeellos is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 5 hours ago
zeelloszeellos
61
New contributor
zeellos is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 5 hours ago
zeelloszeellos
61
asked 5 hours ago
zeelloszeellos
61
61
New contributor
zeellos is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
zeellos is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
zeellos is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$begingroup$
Your plots are slightly different in scale, consider using a fixed range for y-axis (plt.ylim([80,100]) or [0,100] would be best
$endgroup$
– Pedro Henrique Monforte
2 hours ago
add a comment |
$begingroup$
Your plots are slightly different in scale, consider using a fixed range for y-axis (plt.ylim([80,100]) or [0,100] would be best
$endgroup$
– Pedro Henrique Monforte
2 hours ago
$begingroup$
Your plots are slightly different in scale, consider using a fixed range for y-axis (plt.ylim([80,100]) or [0,100] would be best
$endgroup$
– Pedro Henrique Monforte
2 hours ago
$begingroup$
Your plots are slightly different in scale, consider using a fixed range for y-axis (plt.ylim([80,100]) or [0,100] would be best
$endgroup$
– Pedro Henrique Monforte
2 hours ago
add a comment |
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$begingroup$
Your plots are slightly different in scale, consider using a fixed range for y-axis (plt.ylim([80,100]) or [0,100] would be best
$endgroup$
– Pedro Henrique Monforte
2 hours ago