Training custom sklearn classifier with TPOTClassifier?

I created a custom sklearn classifier and need to run it along with tpot. But while running tpot I get this warning.

> Warning: MeanClassifier is not available and will not be used by TPOT.

My full toy code.

```
from tpot import TPOTClassifier
import numpy as np
from sklearn.base import BaseEstimator, ClassifierMixin

class MeanClassifier(BaseEstimator, ClassifierMixin):
def __init__(self):
pass

def fit(self, X, y=None):
self.treshold_ = (sum(X)/len(X))
return self

def _meaning(self, x):
return( True if x >= self.treshold_ else False )

def predict(self, X, y=None):
try:
getattr(self, "treshold_")
except AttributeError:
raise RuntimeError("You must train classifer before predicting data!")

return([self._meaning(x) for x in X])

def score(self, X, y=None):
# counts number of values bigger than mean
return(sum(self.predict(X)))

tpot_config = {
'MeanClassifier': {
},
}

X_train = [i for i in range(0, 100, 5)]
X_test = [i + 3 for i in range(-5, 95, 5)]
y_train = None
y_test= None

tpot = TPOTClassifier(generations=2, population_size=20, verbosity=2, random_state=42,config_dict=tpot_config)
tpot.fit(X_train, y_train)
print(tpot.score(X_test, y_test))
```

How can we run a custom sklearn estimator with TPOT? In the web there is not much info available for running custom models with tpot.