All Questions
6 questions
0votes
0answers
76views
Loss increasing and accuracy decreasing
I've implemented a shallow FC feedforward neural net with 2 input nodes, 1 hidden layer with 4 nodes (tanh activation) and 1 outputnode with sigmoid activation function and binary cross-entropy loss. ...
1vote
0answers
72views
Can you estimate average precision from log loss?
I am doing my final thesis in the field of Deepfakes and their detection. The final outcome is to have a binary classifier which could predict which video was updated and which was not. In other words,...
3votes
1answer
4kviews
Keras: How to connect a CNN model with a decision tree
I want to train a model to predict one's emotion from the physical signals. I have a physical signal and using it as input feature; ecg(Electrocardiography) I want to use the CNN architecture to ...
5votes
2answers
5kviews
Sci-kit learn function to select threshold for higher recall than precision
When we care more that there should be no false negatives, as far as possible… ie. higher recall (video is suitable for kid or not), we should use (receiver operating characteristic) ROC (area under ...
1vote
2answers
101views
What can be done to increase the accuracy of a biological dataset? [closed]
I have a biological unbalanced dataset on which I have applied deep learning, Support Vector Machine (all the kernel functions) and Artificial Neural network for multiclass classification (size: 139 ...
- 1,161
11votes
3answers
9kviews
What cost function and penalty are suitable for imbalanced datasets?
For an imbalanced data set, is it better to choose an L1 or L2 regularization? Is there a cost function more suitable for imbalanced datasets to improve the model score (...
- 111
