<div dir="ltr">Hi Jinwoo<div><br></div><div>It is true that scikit-learn has many models for supervised classification tasks, and it should be relatively trivial for you to munge your 3 data files into the X (data) y (labels) format required for these methods. Examples are k-means, Support Vector Machines, Decision Trees, and Discriminant Analysis. However, these are typically considered "machine learning" techniques; when someone says "AI", they typically mean a Neural Network. If you wish to use scikit-learn for Neural Network classification, you are limited to the Multilayer Perceptron: <a href="http://scikit-learn.org/stable/modules/neural_networks_supervised.html#">http://scikit-learn.org/stable/modules/neural_networks_supervised.html#</a>. If you want to be able to use more advanced Neural Networks, here are some options:</div><div><strong style="color:rgb(29,31,34);font-family:Helvetica,Arial,sans-serif;font-size:14.4px"><br></strong></div><div><strong style="color:rgb(29,31,34);font-family:Helvetica,Arial,sans-serif;font-size:14.4px">Deep neural networks etc.</strong><br></div><div><ul class="gmail-simple" style="padding:0px;margin:0px 0px 10px 25px;color:rgb(29,31,34);font-family:Helvetica,Arial,sans-serif;font-size:14.4px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial"><li style="line-height:1.5em"><a class="gmail-reference external" href="http://deeplearning.net/software/pylearn2/" style="color:rgb(40,120,162);text-decoration:none;word-wrap:break-word">pylearn2</a><span> </span>A deep learning and neural network library build on theano with scikit-learn like interface.</li><li style="line-height:1.5em"><a class="gmail-reference external" href="http://sklearn-theano.github.io/" style="color:rgb(5,87,129);text-decoration:underline;word-wrap:break-word;outline:0px">sklearn_theano</a><span> </span>scikit-learn compatible estimators, transformers, and datasets which use Theano internally</li><li style="line-height:1.5em"><a class="gmail-reference external" href="https://github.com/dnouri/nolearn" style="color:rgb(40,120,162);text-decoration:none;word-wrap:break-word">nolearn</a><span> </span>A number of wrappers and abstractions around existing neural network libraries</li><li style="line-height:1.5em"><a class="gmail-reference external" href="https://github.com/fchollet/keras" style="color:rgb(40,120,162);text-decoration:none;word-wrap:break-word">keras</a><span> </span>Deep Learning library capable of running on top of either TensorFlow or Theano.</li><li style="line-height:1.5em"><a class="gmail-reference external" href="https://github.com/Lasagne/Lasagne" style="color:rgb(40,120,162);text-decoration:none;word-wrap:break-word">lasagne</a><span> </span>A lightweight library to build and train neural networks in Theano.</li></ul>
I personally use Google's TensorFlow. Hope this helps.</div><div><br></div><div>Andrew</div></div><div class="gmail_extra"><br clear="all"><div><div class="gmail_signature" data-smartmail="gmail_signature"><div dir="ltr"><div><div dir="ltr"><div dir="ltr"><div dir="ltr"><~~~~~~~~~~~~~~~~~~~~~~~~~~~><br>J. Andrew Howe, PhD</div><div dir="ltr"><a href="http://www.linkedin.com/in/ahowe42" target="_blank">LinkedIn Profile</a></div><div><a href="http://www.researchgate.net/profile/John_Howe12/" target="_blank">ResearchGate Profile</a></div><div dir="ltr"><a href="http://orcid.org/0000-0002-3553-1990" target="_blank">Open Researcher and Contributor ID (ORCID)</a></div><div dir="ltr"><a href="http://github.com/ahowe42" target="_blank">Github Profile</a><br><div><a href="http://www.andrewhowe.com" target="_blank">Personal Website</a></div><div>I live to learn, so I can learn to live. - me<br></div><div><~~~~~~~~~~~~~~~~~~~~~~~~~~~></div></div></div></div></div></div></div></div>
<br><div class="gmail_quote">On Thu, Mar 29, 2018 at 7:06 AM, PARK Jinwoo <span dir="ltr"><<a href="mailto:jinwoo412@gmail.com" target="_blank">jinwoo412@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><span style="color:rgb(49,49,49);word-spacing:1px;background-color:rgb(255,255,255)">Dear scikit-learn experts</span><br style="color:rgb(49,49,49);word-spacing:1px"><br style="color:rgb(49,49,49);word-spacing:1px"><span style="color:rgb(49,49,49);word-spacing:1px;background-color:rgb(255,255,255)">Hello, I am a graduate school student majoring in doping control</span><br style="color:rgb(49,49,49);word-spacing:1px"><span style="color:rgb(49,49,49);word-spacing:1px;background-color:rgb(255,255,255)">analysis in Korea.</span><br style="color:rgb(49,49,49);word-spacing:1px"><span style="color:rgb(49,49,49);word-spacing:1px;background-color:rgb(255,255,255)">Now I'm in a research institute that carries out doping control analyses.</span><br style="color:rgb(49,49,49);word-spacing:1px"><br style="color:rgb(49,49,49);word-spacing:1px"><span style="color:rgb(49,49,49);word-spacing:1px;background-color:rgb(255,255,255)">I received a project by my advising doctor. It's about operating an AI project.</span><br style="color:rgb(49,49,49);word-spacing:1px"><span style="color:rgb(49,49,49);word-spacing:1px;background-color:rgb(255,255,255)">A workshop is scheduled in April, so it needs to be done in a month.</span><br style="color:rgb(49,49,49);word-spacing:1px"><span style="color:rgb(49,49,49);word-spacing:1px;background-color:rgb(255,255,255)">However, I haven't learn computer science at all and I'm totally ignorant of it.</span><br style="color:rgb(49,49,49);word-spacing:1px"><span style="color:rgb(49,49,49);word-spacing:1px;background-color:rgb(255,255,255)">So I desperately need your advice.</span><br style="color:rgb(49,49,49);word-spacing:1px"><br style="color:rgb(49,49,49);word-spacing:1px"><span style="color:rgb(49,49,49);word-spacing:1px;background-color:rgb(255,255,255)">To be specific, the 3 xml files shown in the picture are analysis results</span><br style="color:rgb(49,49,49);word-spacing:1px"><span style="color:rgb(49,49,49);word-spacing:1px;background-color:rgb(255,255,255)">named positive, negative, and unknown from top to bottom.</span><br style="color:rgb(49,49,49);word-spacing:1px"><span style="color:rgb(49,49,49);word-spacing:1px;background-color:rgb(255,255,255)">We'd like to let AI learn positive and negative data,</span><br style="color:rgb(49,49,49);word-spacing:1px"><span style="color:rgb(49,49,49);word-spacing:1px;background-color:rgb(255,255,255)">input unknown datum, and then see what result will turn out.</span><br style="color:rgb(49,49,49);word-spacing:1px"><br style="color:rgb(49,49,49);word-spacing:1px"><span style="color:rgb(49,49,49);word-spacing:1px;background-color:rgb(255,255,255)">I came to know that there's a module called 'iris calssification' in</span><br style="color:rgb(49,49,49);word-spacing:1px"><span style="color:rgb(49,49,49);word-spacing:1px;background-color:rgb(255,255,255)">scikit-learn</span><br style="color:rgb(49,49,49);word-spacing:1px"><span style="color:rgb(49,49,49);word-spacing:1px;background-color:rgb(255,255,255)">and I'm thinking of utilizing that as it seems similar with my assignment</span><br style="color:rgb(49,49,49);word-spacing:1px"><span style="color:rgb(49,49,49);word-spacing:1px;background-color:rgb(255,255,255)">However, while the database of iris is a csv file with 150 data and</span><br style="color:rgb(49,49,49);word-spacing:1px"><span style="color:rgb(49,49,49);word-spacing:1px;background-color:rgb(255,255,255)">labels inside,</span><br style="color:rgb(49,49,49);word-spacing:1px"><span style="color:rgb(49,49,49);word-spacing:1px;background-color:rgb(255,255,255)">what I have are 3 xml files each one of which represents one data,</span><br style="color:rgb(49,49,49);word-spacing:1px"><span style="color:rgb(49,49,49);word-spacing:1px;background-color:rgb(255,255,255)">which are stored in C:\Users\Jinwoo\Documents\Pyth</span><span style="color:rgb(49,49,49);word-spacing:1px;background-color:rgb(255,255,255)"><wbr>on Scripts\mzdata</span><br style="color:rgb(49,49,49);word-spacing:1px"><span style="color:rgb(49,49,49);word-spacing:1px;background-color:rgb(255,255,255)">The training process is not shuffling randomly the 150 data and</span><br style="color:rgb(49,49,49);word-spacing:1px"><span style="color:rgb(49,49,49);word-spacing:1px;background-color:rgb(255,255,255)">dividing into training set and test set. The data are already assigned</span><br style="color:rgb(49,49,49);word-spacing:1px"><span style="color:rgb(49,49,49);word-spacing:1px;background-color:rgb(255,255,255)">into training ones and testing one.</span><br style="color:rgb(49,49,49);word-spacing:1px"><span style="color:rgb(49,49,49);word-spacing:1px;background-color:rgb(255,255,255)">Also, when training the program, training labels naming positive and</span><br style="color:rgb(49,49,49);word-spacing:1px"><span style="color:rgb(49,49,49);word-spacing:1px;background-color:rgb(255,255,255)">negative should be inserted on my own.</span><br style="color:rgb(49,49,49);word-spacing:1px"><br style="color:rgb(49,49,49);word-spacing:1px"><span style="color:rgb(49,49,49);word-spacing:1px;background-color:rgb(255,255,255)">What I know all is that it will be appropriate to use fit() function</span><br style="color:rgb(49,49,49);word-spacing:1px"><span style="color:rgb(49,49,49);word-spacing:1px;background-color:rgb(255,255,255)">and predict() function to train and test.</span><br style="color:rgb(49,49,49);word-spacing:1px"><span style="color:rgb(49,49,49);word-spacing:1px;background-color:rgb(255,255,255)">But I have no idea on what to import, how to write codes correctly, and so on</span><br style="color:rgb(49,49,49);word-spacing:1px"><br style="color:rgb(49,49,49);word-spacing:1px"><span style="color:rgb(49,49,49);word-spacing:1px;background-color:rgb(255,255,255)"><div dir="auto">It will be thankful to give me some help.</div></span><a href="https://mail.python.org/mailman/listinfo/scikit-learn" rel="noreferrer" style="font-size:1rem;word-spacing:1px" target="_blank"><div dir="auto"><br></div></a>
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