title: ValueError in DecisionTreeClassifier
body: <p>Here's the link of the decision tree implementation I used.
  <a href="https://www.geeksforgeeks.org/decision-tree-implementation-python/" rel="nofollow noreferrer">https://www.geeksforgeeks.org/decision-tree-implementation-python/</a></p>
  <p>And my dataframe is only composed of &quot;A&quot; and &quot;B&quot; with 512 values for each of them.</p>
  <pre><code>data
  
      1   2   ...      509     510    511    512
  A   0.005190    0.00173 ... 0.001730    0.000577    0.002884    0.000577
  A   0.000597    0.006567 ... 0.000597   0.000597    0.001194    0.001194
  B   0.000582    0.010477 ... 0.001746   0.001164    0.001243    0.003108
  A   0.009323    0.001865 ... 0.001865   0.001243    0.003108    0.000622
  A   0.000531    0.003186 ... 0.003186   0.001593    0.002124    0.001062
  
  ...
  </code></pre>
  <pre><code>X = data.values[:, 1:5]
  Y = data.values[:, 0]
  
  X_train, X_test, y_train, y_test = train_test_split(X, Y, test_size = 0.3, random_state = 100)
  
  clf_gini = DecisionTreeClassifier(criterion = &quot;gini&quot;, random_state = 100,max_depth=3, min_samples_leaf=5)
  clf_gini.fit(X_train, y_train)
  </code></pre>
  <p>However, it ran into a valueerror in the last line of code when I call the <code>fit</code> function. It does't work either even if I changed the value of parameters.</p>
  <pre><code>ValueError                                Traceback (most recent call last)
  &lt;ipython-input-19-484db0a3d479&gt; in &lt;module&gt;
        1 # Train with gini
        2 clf_gini = DecisionTreeClassifier(criterion = &quot;gini&quot;, random_state = 100,max_depth=3, min_samples_leaf=5)
  ----&gt; 3 clf_gini.fit(X_train, y_train)
  
  ~\anaconda3\envs\myenv\lib\site-packages\sklearn\tree\_classes.py in fit(self, X, y, sample_weight, check_input, X_idx_sorted)
      901         &quot;&quot;&quot;
      902 
  --&gt; 903         super().fit(
      904             X, y,
      905             sample_weight=sample_weight,
  
  ~\anaconda3\envs\myenv\lib\site-packages\sklearn\tree\_classes.py in fit(self, X, y, sample_weight, check_input, X_idx_sorted)
      189 
      190         if is_classification:
  --&gt; 191             check_classification_targets(y)
      192             y = np.copy(y)
      193 
  
  ~\anaconda3\envs\myenv\lib\site-packages\sklearn\utils\multiclass.py in check_classification_targets(y)
      181     if y_type not in ['binary', 'multiclass', 'multiclass-multioutput',
      182                       'multilabel-indicator', 'multilabel-sequences']:
  --&gt; 183         raise ValueError(&quot;Unknown label type: %r&quot; % y_type)
      184 
      185 
  
  ValueError: Unknown label type: 'continuous'
  </code></pre>
  <p>I'm honestly so confused. Can someone help me out on this? Appreciate it.</p>