On Wed, Apr 5, 2017 at 8:27 AM, Oleksandr Zaytsev <olk.zayt...@gmail.com> wrote:
> Hello! > > Several weeks ago I've announced my NeuralNetworks project. Thank you very > much for your ideas and feedback. As suggested, I wrote examples for every > class and tested my perceptron on linearly-separable logical functions. > > I have just completed a post about my implementation of a single-layer > perceptron: https://medium.com/@i.oleks/single-layer-perceptron-in-pharo > -5b13246a041d. It has a detailed explanation of every part of the design > and illustrates different approaches to implementation. > > Please, tell me what you think. > > Are my class diagrams correct or did I mess something up? > Is there a design pattern that I should consider? > Do you think that I should do something differently? > Should I improve the quality of my code? > > Yours sincerely, > Oleksandr > Hi Oleks, (sorry for the delayed response. Saw you other post in pharo-dev and found this sitting in my drafts from last week.) Nice article and interesting read. I only did NeuralNetworks in my undergrad 25 years ago so my knowledge is a bit vague. I think you design reasoning is fine for this stage. Down the track you might consider that OO is about hiding implementation details. So just a vague idea, you might have SLPerceptron storing neuron data internally in arrays that a GPU can process efficiently, but when "SLPerceptron>>#at:" is asked for a neuron, it constructs a "real" neuron object, whose methods forward to the arrays in theSLPerceptron. cheers -ben
