Part of my research work is to classify sensor data on Android using Multilayer Perceptron (MLP) classifier.
I used WekaSTRIPPED to train (build) the MLP classifier on the phone and save the trained model on the sdcard by serializing it. This works fine in a small scale problem even with large training data. I mean by small scale problem that the MLP model to be trained consists of about 10 inputs (features) and 4 outputs (classes). However, when the MLP model increases to have 25 inputs and 10 outputs the building process fails on the phone. I tried to increase the heap size to 1024 m but unfortunately this doesn’t solve the problem. I also tried to build the classifier on a virtual machine but again this doesn’t solve the problem.
Another trial was to train the model using WEKA on the PC and then serialize the model to a specific place on the machine. I copied this saved model from the pc and pasted it on the sdcard of the phone. Then I deserialized this model using Weka for Android but unfortunately, the deserialization of the model fails.
My question here is do I really need to train (build) my classifier on the phone specially that my training data is supposed to be very large and even the model to be trained itself is going to be more and more complex?
Any help is greatly appreciated.
Thanks.
Part of my research work is to classify sensor data on Android using Multilayer Perceptron (MLP) classifier.
I used WekaSTRIPPED to train (build) the MLP classifier on the phone and save the trained model on the sdcard by serializing it. This works fine in a small scale problem even with large training data. I mean by small scale problem that the MLP model to be trained consists of about 10 inputs (features) and 4 outputs (classes). However, when the MLP model increases to have 25 inputs and 10 outputs the building process fails on the phone. I tried to increase the heap size to 1024 m but unfortunately this doesn’t solve the problem. I also tried to build the classifier on a virtual machine but again this doesn’t solve the problem.
Another trial was to train the model using WEKA on the PC and then serialize the model to a specific place on the machine. I copied this saved model from the pc and pasted it on the sdcard of the phone. Then I deserialized this model using Weka for Android but unfortunately, the deserialization of the model fails.
My question here is do I really need to train (build) my classifier on the phone specially that my training data is supposed to be very large and even the model to be trained itself is going to be more and more complex?
Any help is greatly appreciated.
Thanks.