from abc import ABC, abstractmethod


class MLModel(ABC):
    x_train = None
    y_train = None

    def __init__(self):
        pass

    @abstractmethod
    def fit(self, x_train, y_train=None):
        pass

    @abstractmethod
    def transform(self):
        pass

    @abstractmethod
    def predict(self):
        pass

    @abstractmethod
    def fit_predict(self, x_train):
        pass

bb19ec6ec178d1ef706571db616b8b040a2316f6
<mask token>


class MLModel(ABC):
    <mask token>
    <mask token>

    def __init__(self):
        pass
    <mask token>

    @abstractmethod
    def transform(self):
        pass

    @abstractmethod
    def predict(self):
        pass

    @abstractmethod
    def fit_predict(self, x_train):
        pass

<mask token>


class MLModel(ABC):
    <mask token>
    <mask token>

    def __init__(self):
        pass

    @abstractmethod
    def fit(self, x_train, y_train=None):
        pass

    @abstractmethod
    def transform(self):
        pass

    @abstractmethod
    def predict(self):
        pass

    @abstractmethod
    def fit_predict(self, x_train):
        pass

<mask token>


class MLModel(ABC):
    x_train = None
    y_train = None

    def __init__(self):
        pass

    @abstractmethod
    def fit(self, x_train, y_train=None):
        pass

    @abstractmethod
    def transform(self):
        pass

    @abstractmethod
    def predict(self):
        pass

    @abstractmethod
    def fit_predict(self, x_train):
        pass

from abc import ABC, abstractmethod


class MLModel(ABC):
    x_train = None
    y_train = None

    def __init__(self):
        pass

    @abstractmethod
    def fit(self, x_train, y_train=None):
        pass

    @abstractmethod
    def transform(self):
        pass

    @abstractmethod
    def predict(self):
        pass

    @abstractmethod
    def fit_predict(self, x_train):
        pass
