title: I am trying to make my data balance as my target variable has multi-class and i want to oversample it to make my data balance
body: <p><code>print(x)'
  </code>Here "x" is Independent Variables.`</p>
  
  <pre><code>    Restaurant  Cuisines    Average_Cost    Rating  Votes   Reviews Area
      0   3.526361    0.693147    5.303305    1.504077    2.564949    1.609438    7.214504
      1   1.386294    4.127134    4.615121    1.504077    2.484907    1.609438    5.905362
      2   2.772589    1.386294    5.017280    1.526056    4.605170    3.433987    6.131226
      3   3.912023    2.833213    5.525453    1.547563    5.176150    4.564348    7.643483
      4   3.526361    2.708050    5.303305    1.435085    5.948035    5.046646    6.126869
      ... ... ... ... ... ... ... ...
      11089   3.912023    0.693147    5.525453    1.648659    5.789960    5.046646    3.135494
      11090   1.386294    6.028279    4.615121    1.526056    3.610918    2.833213    7.643483
      11091   1.386294    2.397895    4.615121    1.504077    3.828641    2.944439    5.814131
      11092   1.386294    6.028279    4.615121    1.410987    3.218876    2.302585    5.905362
      11093   1.386294    6.028279    4.615121    1.029619    0.000000    0.000000    5.564520
      11094 rows × 7 columns
  </code></pre>
  
  <pre><code>`print(y.value_counts()) `
  </code></pre>
  
  <p>Here "y" is target variable and it has multi-class. </p>
  
  <pre><code>    30 minutes     7406
      45 minutes     2665
      65 minutes      923
      120 minutes      62
      20 minutes       20
      80 minutes       14
      10 minutes        4
      Name: Delivery_Time, dtype: int64
  </code></pre>
  
  <p>After exploring the TARGET VARIABLE WE CAN SEE THAT "30 MINUTES" CLASS HAS HIGHER COUNTS AMONG OTHER CLASS.</p>
  
  <pre><code>FOR FOR MAKING THINGS BALANCE I TRIED SMOTEtomek to oversamplemy data and make it balance. Below are the codes provide and got error.
  
  from imblearn.combine import SMOTEtomek
  smk = SMOTEtomek(ratio = 1)
  x_res, y_res = smk.fit_sample(x,y)
  
  ---------------------------------------------------------------------------
  ValueError                                Traceback (most recent call last)
  &lt;ipython-input-54-426e8b86623d&gt; in &lt;module&gt;()
        1 from imblearn.combine import SMOTETomek
        2 smk = SMOTETomek(ratio = 1)
  ----&gt; 3 x_res, y_res = smk.fit_sample(x,y)
  
  2 frames
  /usr/local/lib/python3.6/dist-packages/imblearn/utils/_validation.py in _sampling_strategy_float(sampling_strategy, y, sampling_type)
      311     if type_y != 'binary':
      312         raise ValueError(
  --&gt; 313             '"sampling_strategy" can be a float only when the type '
      314             'of target is binary. For multi-class, use a dict.')
      315     target_stats = _count_class_sample(y)
  
  ValueError: "sampling_strategy" can be a float only when the type of target is binary. For multi-class, use a dict.
  </code></pre>