Folders
Models: Stores previousely trained models File names will be a shorthand for the model details that is TBD
RawInput Input files to be classified
Software Python files
TrainingData Prelabelled data for model training
Root Files models.csv : Record of previous training results storing model details for easy review, info will probably be redundant with filename shorthand train.bat to execute training
TODO: Determine model naming convention Develop model trainers Probably a text or csv file to configure model generation parameters for testing
Resources: Statistics https://medium.com/analytics-vidhya/confusion-matrix-accuracy-precision-recall-f1-score-ade299cf63cd
Final work plan: Data reading: Read CSV files To start will will differentiate collagen and Epithelium since we don't have cancer data yet, or maybe get all the possible classes we'll see We still start with just the convolutional neural network So read data -> Pass to model -> Generate and test model, all like previous project (just different data and different input layer) Note on data, first column appears to be the wavelength and second column the actual data, so the second is the only used for classification If we have time do the encoder