Improve and compare the performance of an existing deep learning model
Budget: $30 – $250 CAD
Currently I have a deep learning model that uses PCA to reduce the features and pass it through a feed-forward neural network to classify the data.
I would like to someone to help me assess to the performance of the model:
1. optimize hyperparameters
2. test the performance of the model without PCA
3. test the performance of the model with a feature reduction technique that demonstrates feature importance
4. compare the performance of this deep learning model with other existing classification methods like extra tree, KNN, random forest, SGD classifier and SVM in terms of accuracy
I would like to someone to help me assess to the performance of the model:
1. optimize hyperparameters
2. test the performance of the model without PCA
3. test the performance of the model with a feature reduction technique that demonstrates feature importance
4. compare the performance of this deep learning model with other existing classification methods like extra tree, KNN, random forest, SGD classifier and SVM in terms of accuracy