In this report, we devise a methodology for identifying the species of an iris amongst 3 based on 4 distinctive features. We first cover the constitution of the data set and input patterns. We then determine the layout and structure of the neural network we will use for the classification. We continue by testing the network in real life conditions. We conclude with a review of the methods used, and how they could be improved.

iris-classification-matlab-master
.................................\LICENSE
.................................\README
.................................\Report.pdf
.................................\checkNetwork.m
.................................\classifyIris.m
.................................\createNetwork.m
.................................\importIris.m
.................................\importIrisToClassify.m
.................................\irisPlot.m
.................................\iristestdata.csv
.................................\iristrainingdata.csv
.................................\nameIrises.m
.................................\noiseValues.m
.................................\plotLearningRate.m
.................................\variateEpochs.m
.................................\variateHiddenUnits.m
.................................\variateMinGrad.m

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