I am trying to plot a graph which makes sense to me, which is difficult to crunch in a single function, but let's say I want to see numeric data and labels as legends of this data to start with and then according to my professor I have to use different techniques to make the machine learn something new from the data, which is the tougher part.
The problem with my simplistic code is that I have no way of telling Octave that iris_data_1 and labels are just different columns of a single matrix that consists of different data types, so I had to tinker using a spreadsheet solution a process that I would have to automate later.
I ran:
addpath('...')
load('iris-data-1.dat')
load('iris-data-label.dat')
plot(...) //this is the part that is tough, because I do not know how to link the data so that the iris-data-label.dat file appears as a legend on the y axis.
plot(mean(íris-data)
//this seems to work, I am not sure how to measure the accuracy though.
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Jonathan Camilleri
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