text: Title: Polynomial Feaatures + SklearnWrapper weird behavior
  Body: **Describe the bug**
  A clear and concise description of what the bug is.
  
  When using PolynomialFeaturs + SklearnWrappers the base features are duplicated, when trying to dedup using DropDuplicateFeatures the values are repeated again!!
  
  Using the simple Titanic Dataset you can run something like this:
  
  ```python
  df = pd.read_csv('https://www.openml.org/data/get_csv/16826755/phpMYEkMl')
  X = df[['pclass','sex','age','fare','embarked']]
  y = df.survived
  
  X_train, X_val, y_train, y_val = train_test_split(X, y, test_size=0.2, random_state=42)
  pipe = Pipeline(steps = [
      ('ci', CategoricalImputer(imputation_method='frequent')),
      ('mmi', MeanMedianImputer(imputation_method='mean')),
      ('od', OrdinalEncoder(encoding_method='arbitrary')),
      ('pl', SklearnTransformerWrapper(PolynomialFeatures(degree = 2, interaction_only = True, include_bias=False), variables=['pclass','sex'])),
      #('drop', DropDuplicateFeatures()),
      #('sc', SklearnTransformerWrapper(StandardScaler(), variables=['Age','Fare'])),
      #('lr', LogisticRegression(random_state=42))
  
  ])
  pipe.fit_transform(X_train)
  ```
  
  This returns the first issue:  
  
  ![image](https://user-images.githubusercontent.com/48638337/180299902-4f0bf6c2-e4ea-419a-9768-245c45d5df29.png)
  
  I'm getting pclass and sex duplicated, I'm expecting to get back only interactions. This is expected from [Sklearn Docs](https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.PolynomialFeatures.html) but why would I want duplicated features?
  
  Looking into Feature Engine Docs I found `DropDuplicateFeatures()`, but if applying into the Pipeline I get this:
  
  ```python
  df = pd.read_csv('https://www.openml.org/data/get_csv/16826755/phpMYEkMl')
  X = df[['pclass','sex','age','fare','embarked']]
  y = df.survived
  
  X_train, X_val, y_train, y_val = train_test_split(X, y, test_size=0.2, random_state=42)
  pipe = Pipeline(steps = [
      ('ci', CategoricalImputer(imputation_method='frequent')),
      ('mmi', MeanMedianImputer(imputation_method='mean')),
      ('od', OrdinalEncoder(encoding_method='arbitrary')),
      ('pl', SklearnTransformerWrapper(PolynomialFeatures(degree = 2, interaction_only = True, include_bias=False), variables=['pclass','sex'])),
      ('drop', DropDuplicateFeatures()),
      #('sc', SklearnTransformerWrapper(StandardScaler(), variables=['Age','Fare'])),
      #('lr', LogisticRegression(random_state=42))
  
  ])
  pipe.fit_transform(X_train)
  ```
  ![image](https://user-images.githubusercontent.com/48638337/180300357-209703e8-51c9-420f-bf79-71b67760304d.png)
  
  getting tons of repeated features, which is totally unexpected.
  
  
  
  
  
  **Expected behavior**
  Not getting repeated/duplicated features.
  
  **Screenshots**
  Shown above.
  
  **Desktop (please complete the following information):**
   - Ubuntu 20.04
   - Feature Engine 1.4.0
  
  
  Thanks in Advance, 
  
  Alfonso
  