selection of features and hyperparameters of the model

How to use feature selection together with hyperparameter selection of a classifier model?

```
gene_space = [
    {'low': 1, 'high': 200, 'step': 3}, # n_estimators
    {'low': 1, 'high': 7, 'step': 1}, # depth
    # Feature selection (binary vector for each feature)
    *([0, 1] * (n_features // 2))
    #*[random.randint(0, 1) for _ in  range(n_features)]
]
```

