I am doing a case study on Boston House data to predict price using QNN with following steps
- PCA to select features, selected upto 8 features
- Standardsxalwer to scale data
- AngleEmbedding to encode data
- StronglyEntanglingLayers as the quantum layer alongwith 2 Keras layers
- Adam optimizer
- default.qubit and default.qubit.tf as the device
But the Accuracy is very low , please advise any pointers by which the accuracy could be improved any better QNN layers or Optimizer or architecture ?
Also please advise is their any physical device one can use for experimentation ?