title: Add legend names to a SVM plot in matplotlib
body: <p>I made a SVM plot from the Iris-dataset by using matplotlib and mlxtend in Jupyter notebook. I am trying to get the Species name on the legend of the plot instead of 0, 1 and 2. So far my code is :</p>
  
  <pre><code>from sklearn import svm
  from mlxtend.plotting import plot_decision_regions
  
  X = iris[['SepalLengthCm', 'SepalWidthCm']]
  y = iris['SpecieID']
  
  clf = svm.SVC(decision_function_shape = 'ovo')
  clf.fit(X.values, y.values) 
  
  # Plot Decision Region using mlxtend's awesome plotting function
  plot_decision_regions(X=X.values, 
                        y=y.values,
                        clf=clf, 
                        legend=2)
  
  # Update plot object with X/Y axis labels and Figure Title
  plt.xlabel(X.columns[0], size=14)
  plt.ylabel(X.columns[1], size=14)
  plt.title('SVM Decision Region Boundary', size=16)
  </code></pre>
  
  <p>And results in this plot : <a href="https://i.stack.imgur.com/psDcC.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/psDcC.png" alt="enter image description here"></a></p>
  
  <p>I couldn't find how to replace 0,1 and 2 by the species names (Iris-setosa, Iris-versicolor and Iris-virginica).</p>
  
  <p>I created the pandas DataFrame by :</p>
  
  <pre><code>import pandas as pd
  iris = pd.read_csv("Iris.csv") # the iris dataset is now a Pandas DataFrame
  iris = iris.assign(SepalRatio = iris['SepalLengthCm'] / iris['SepalWidthCm']).assign(PetalRatio = iris['PetalLengthCm'] / iris['PetalWidthCm']).assign(SepalMultiplied = iris['SepalLengthCm'] * iris['SepalWidthCm']).assign(PetalMultiplied = iris['PetalLengthCm'] * iris['PetalWidthCm'])
  d = {"Iris-setosa" : 0, "Iris-versicolor": 1, "Iris-virginica": 2}
  iris['SpecieID'] = iris['Species'].map(d).fillna(-1)
  </code></pre>