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2017-11-26 11:34:59 +01:00

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<center><h1>Data Analysis and Machine Learning: Representing data</h1></center> <!-- document title -->
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<!-- author(s): Morten Hjorth-Jensen -->
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<b>Morten Hjorth-Jensen</b> [1, 2]
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<!-- institution(s) -->
<center>[1] <b>Department of Physics, University of Oslo</b></center>
<center>[2] <b>Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University</b></center>
<br>
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<center><h4>Nov 26, 2017</h4></center> <!-- date -->
<br>
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<!-- !split --><br><br><br><br><br><br><br><br><br><br>
<h2 id="___sec0">Representing data, overarching aims </h2>
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<b></b>
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<!-- code=python (!bc pycod) typeset with pygments style "default" -->
<div class="highlight" style="background: #f8f8f8"><pre style="line-height: 125%"><span></span><span style="color: #008000; font-weight: bold">import</span> <span style="color: #0000FF; font-weight: bold">numpy</span> <span style="color: #008000; font-weight: bold">as</span> <span style="color: #0000FF; font-weight: bold">np</span>
<span style="color: #008000; font-weight: bold">import</span> <span style="color: #0000FF; font-weight: bold">matplotlib.pyplot</span> <span style="color: #008000; font-weight: bold">as</span> <span style="color: #0000FF; font-weight: bold">plt</span>
<span style="color: #008000; font-weight: bold">from</span> <span style="color: #0000FF; font-weight: bold">scipy</span> <span style="color: #008000; font-weight: bold">import</span> sparse
<span style="color: #008000; font-weight: bold">import</span> <span style="color: #0000FF; font-weight: bold">pandas</span> <span style="color: #008000; font-weight: bold">as</span> <span style="color: #0000FF; font-weight: bold">pd</span>
<span style="color: #008000; font-weight: bold">from</span> <span style="color: #0000FF; font-weight: bold">IPython.display</span> <span style="color: #008000; font-weight: bold">import</span> display
eye <span style="color: #666666">=</span> np<span style="color: #666666">.</span>eye(<span style="color: #666666">4</span>)
<span style="color: #008000; font-weight: bold">print</span>(eye)
sparse_mtx <span style="color: #666666">=</span> sparse<span style="color: #666666">.</span>csr_matrix(eye)
<span style="color: #008000; font-weight: bold">print</span>(sparse_mtx)
x <span style="color: #666666">=</span> np<span style="color: #666666">.</span>linspace(<span style="color: #666666">-10</span>,<span style="color: #666666">10</span>,<span style="color: #666666">100</span>)
y <span style="color: #666666">=</span> np<span style="color: #666666">.</span>sin(x)
plt<span style="color: #666666">.</span>plot(x,y,marker<span style="color: #666666">=</span><span style="color: #BA2121">&#39;x&#39;</span>)
plt<span style="color: #666666">.</span>show()
data <span style="color: #666666">=</span> {<span style="color: #BA2121">&#39;Name&#39;</span>: [<span style="color: #BA2121">&quot;John&quot;</span>, <span style="color: #BA2121">&quot;Anna&quot;</span>, <span style="color: #BA2121">&quot;Peter&quot;</span>, <span style="color: #BA2121">&quot;Linda&quot;</span>], <span style="color: #BA2121">&#39;Location&#39;</span>: [<span style="color: #BA2121">&quot;Roma&quot;</span>, <span style="color: #BA2121">&quot;Napoli&quot;</span>, <span style="color: #BA2121">&quot;Torino&quot;</span>, <span style="color: #BA2121">&quot;Milano&quot;</span>], <span style="color: #BA2121">&#39;Age&#39;</span>:[<span style="color: #666666">51</span>, <span style="color: #666666">21</span>, <span style="color: #666666">34</span>, <span style="color: #666666">45</span>]}
data_pandas <span style="color: #666666">=</span> pd<span style="color: #666666">.</span>DataFrame(data)
display(data_pandas)
</pre></div>
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<p>
<!-- !split --><br><br><br><br><br><br><br><br><br><br>
<h2 id="___sec1">Representing data, overarching aims </h2>
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<b></b>
<p>
<p>
<!-- code=python (!bc pycod) typeset with pygments style "default" -->
<div class="highlight" style="background: #f8f8f8"><pre style="line-height: 125%"><span></span><span style="color: #008000; font-weight: bold">import</span> <span style="color: #0000FF; font-weight: bold">numpy</span> <span style="color: #008000; font-weight: bold">as</span> <span style="color: #0000FF; font-weight: bold">np</span>
<span style="color: #008000; font-weight: bold">import</span> <span style="color: #0000FF; font-weight: bold">matplotlib.pyplot</span> <span style="color: #008000; font-weight: bold">as</span> <span style="color: #0000FF; font-weight: bold">plt</span>
<span style="color: #008000; font-weight: bold">from</span> <span style="color: #0000FF; font-weight: bold">scipy</span> <span style="color: #008000; font-weight: bold">import</span> sparse
<span style="color: #008000; font-weight: bold">import</span> <span style="color: #0000FF; font-weight: bold">pandas</span> <span style="color: #008000; font-weight: bold">as</span> <span style="color: #0000FF; font-weight: bold">pd</span>
<span style="color: #008000; font-weight: bold">from</span> <span style="color: #0000FF; font-weight: bold">IPython.display</span> <span style="color: #008000; font-weight: bold">import</span> display
<span style="color: #008000; font-weight: bold">import</span> <span style="color: #0000FF; font-weight: bold">mglearn</span>
<span style="color: #008000; font-weight: bold">import</span> <span style="color: #0000FF; font-weight: bold">sklearn</span>
<span style="color: #008000; font-weight: bold">from</span> <span style="color: #0000FF; font-weight: bold">sklearn.linear_model</span> <span style="color: #008000; font-weight: bold">import</span> LinearRegression
<span style="color: #008000; font-weight: bold">from</span> <span style="color: #0000FF; font-weight: bold">sklearn.tree</span> <span style="color: #008000; font-weight: bold">import</span> DecisionTreeRegressor
x, y <span style="color: #666666">=</span> mglearn<span style="color: #666666">.</span>datasets<span style="color: #666666">.</span>make_wave(n_samples<span style="color: #666666">=100</span>)
line <span style="color: #666666">=</span> np<span style="color: #666666">.</span>linspace(<span style="color: #666666">-3</span>,<span style="color: #666666">3</span>,<span style="color: #666666">1000</span>,endpoint<span style="color: #666666">=</span><span style="color: #008000">False</span>)<span style="color: #666666">.</span>reshape(<span style="color: #666666">-1</span>,<span style="color: #666666">1</span>)
reg <span style="color: #666666">=</span> DecisionTreeRegressor(min_samples_split<span style="color: #666666">=3</span>)<span style="color: #666666">.</span>fit(x,y)
plt<span style="color: #666666">.</span>plot(line, reg<span style="color: #666666">.</span>predict(line), label<span style="color: #666666">=</span><span style="color: #BA2121">&quot;decision tree&quot;</span>)
regline <span style="color: #666666">=</span> LinearRegression()<span style="color: #666666">.</span>fit(x,y)
plt<span style="color: #666666">.</span>plot(line, regline<span style="color: #666666">.</span>predict(line), label<span style="color: #666666">=</span> <span style="color: #BA2121">&quot;Linear Rgression&quot;</span>)
plt<span style="color: #666666">.</span>show()
</pre></div>
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<!-- ------------------- end of main content --------------- -->
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<!-- copyright --> &copy; 1999-2017, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license
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