text: Title: tSNE Value Error when no classes are specified
  Body: See [yellowbrick t-SNE fit raises ValueError](https://stackoverflow.com/questions/48950135/yellowbrick-t-sne-fit-raises-valueerror):
  
  The issue has to do with the way numpy arrays are evaluated in 1.13 - we need to change [yellowbrick.text.tsne Line 256](https://github.com/DistrictDataLabs/yellowbrick/blob/develop/yellowbrick/text/tsne.py#L256) to `if y is not None and self.classes_ is None`
  
  code to produce:
  
  ```python
  import pandas as pd
  from yellowbrick.text import TSNEVisualizer
  from sklearn.datasets import make_classification
  
  ## produce random data
  X, y = make_classification(n_samples=200, n_features=100,
                         n_informative=20, n_redundant=10,
                         n_classes=3, random_state=42)
  
  ## visualize data with t-SNE
  tsne = TSNEVisualizer()
  tsne.fit(X, y)
  tsne.poof()
  ```
  
  error raised:
  
  ```
  Traceback (most recent call last):
    File "t.py", line 12, in <module>
      tsne.fit(X, y)
    File "/Users/benjamin/Workspace/ddl/yellowbrick/yellowbrick/text/tsne.py", line 256, in fit
      if y and self.classes_ is None:
  ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
  ```