"""The model class"""

__author__ = "Ruben R. Kazumov"
__copyright__ = "Copyright 2019, Ruben R. Kazumov"
__credits__ = ["Ruben R. Kazumov"]
__license__ = "MIT"
__version__ = [3, 0, 0]
__maintainer__ = "Ruben R. Kazumov"
__email__ = "kazumov@gmail.com"
__status__ = "Production"

from typing import Union

import keras

from keras.models import Sequential

from keras.layers import Dense, Dropout


class ModelDDDD:
    """Sequential model with layers: Dense->Dropout->Dense->Dense"""

    def __init__(self, featuresCount: int):
        """Parameters:

        - featuresCount (int): A number of features of the data set.
        """
        super().__init__()

        model = Sequential()

        dense1 = int(featuresCount * 0.75)
        dense2 = int(featuresCount * 0.5)

        model.add(Dense(dense1, activation="relu", input_shape=(featuresCount,)))
        model.add(Dropout(0.1))
        model.add(Dense(dense2, activation="relu"))
        model.add(Dense(1, activation="sigmoid"))
        model.compile(
            optimizer="rmsprop", loss="binary_crossentropy", metrics=["accuracy"]
        )
        self.model = model

    def __call__(self) -> Union[Sequential]:
        """A factory method"""
        return self.model

    def summary(self):
        self.model.summary()

db3f739d90f4fec1445f0e13d2e44f00378d1718
<mask token>


class ModelDDDD:
    <mask token>
    <mask token>

    def __call__(self) ->Union[Sequential]:
        """A factory method"""
        return self.model
    <mask token>

<mask token>


class ModelDDDD:
    <mask token>
    <mask token>

    def __call__(self) ->Union[Sequential]:
        """A factory method"""
        return self.model

    def summary(self):
        self.model.summary()

<mask token>
__author__ = 'Ruben R. Kazumov'
__copyright__ = 'Copyright 2019, Ruben R. Kazumov'
__credits__ = ['Ruben R. Kazumov']
__license__ = 'MIT'
__version__ = [3, 0, 0]
__maintainer__ = 'Ruben R. Kazumov'
__email__ = 'kazumov@gmail.com'
__status__ = 'Production'
<mask token>


class ModelDDDD:
    """Sequential model with layers: Dense->Dropout->Dense->Dense"""

    def __init__(self, featuresCount: int):
        """Parameters:

        - featuresCount (int): A number of features of the data set.
        """
        super().__init__()
        model = Sequential()
        dense1 = int(featuresCount * 0.75)
        dense2 = int(featuresCount * 0.5)
        model.add(Dense(dense1, activation='relu', input_shape=(
            featuresCount,)))
        model.add(Dropout(0.1))
        model.add(Dense(dense2, activation='relu'))
        model.add(Dense(1, activation='sigmoid'))
        model.compile(optimizer='rmsprop', loss='binary_crossentropy',
            metrics=['accuracy'])
        self.model = model

    def __call__(self) ->Union[Sequential]:
        """A factory method"""
        return self.model

    def summary(self):
        self.model.summary()

<mask token>
__author__ = 'Ruben R. Kazumov'
__copyright__ = 'Copyright 2019, Ruben R. Kazumov'
__credits__ = ['Ruben R. Kazumov']
__license__ = 'MIT'
__version__ = [3, 0, 0]
__maintainer__ = 'Ruben R. Kazumov'
__email__ = 'kazumov@gmail.com'
__status__ = 'Production'
from typing import Union
import keras
from keras.models import Sequential
from keras.layers import Dense, Dropout


class ModelDDDD:
    """Sequential model with layers: Dense->Dropout->Dense->Dense"""

    def __init__(self, featuresCount: int):
        """Parameters:

        - featuresCount (int): A number of features of the data set.
        """
        super().__init__()
        model = Sequential()
        dense1 = int(featuresCount * 0.75)
        dense2 = int(featuresCount * 0.5)
        model.add(Dense(dense1, activation='relu', input_shape=(
            featuresCount,)))
        model.add(Dropout(0.1))
        model.add(Dense(dense2, activation='relu'))
        model.add(Dense(1, activation='sigmoid'))
        model.compile(optimizer='rmsprop', loss='binary_crossentropy',
            metrics=['accuracy'])
        self.model = model

    def __call__(self) ->Union[Sequential]:
        """A factory method"""
        return self.model

    def summary(self):
        self.model.summary()

"""The model class"""

__author__ = "Ruben R. Kazumov"
__copyright__ = "Copyright 2019, Ruben R. Kazumov"
__credits__ = ["Ruben R. Kazumov"]
__license__ = "MIT"
__version__ = [3, 0, 0]
__maintainer__ = "Ruben R. Kazumov"
__email__ = "kazumov@gmail.com"
__status__ = "Production"

from typing import Union

import keras

from keras.models import Sequential

from keras.layers import Dense, Dropout


class ModelDDDD:
    """Sequential model with layers: Dense->Dropout->Dense->Dense"""

    def __init__(self, featuresCount: int):
        """Parameters:

        - featuresCount (int): A number of features of the data set.
        """
        super().__init__()

        model = Sequential()

        dense1 = int(featuresCount * 0.75)
        dense2 = int(featuresCount * 0.5)

        model.add(Dense(dense1, activation="relu", input_shape=(featuresCount,)))
        model.add(Dropout(0.1))
        model.add(Dense(dense2, activation="relu"))
        model.add(Dense(1, activation="sigmoid"))
        model.compile(
            optimizer="rmsprop", loss="binary_crossentropy", metrics=["accuracy"]
        )
        self.model = model

    def __call__(self) -> Union[Sequential]:
        """A factory method"""
        return self.model

    def summary(self):
        self.model.summary()
