使用SVM而不是NN培训本地模型
我有一个具有数字功能和标签的数据集。我正在使用TensorFlow（TFF）建立一个联合学习模型。 基本上，我拥有的模型是（神经网络），它在TFF教程中始终说明。 我想问是否有机会为当地客户（例如SVM）建立另一个模型？由于它适合我的数据集。
我的神经网络：
def create_keras_model():
initializer = tf.keras.initializers.Zeros()
return tf.keras.models.Sequential([
tf.keras.layers.Input(shape=(18,)),
tf.keras.layers.Dense(128),
tf.keras.layers.Dense(4, kernel_initializer= initializer),
tf.keras.layers.Softmax(),
])
def model_fn():
keras_model = create_keras_model()
return tff.learning.from_keras_model(
keras_model,
input_spec=train_data[0].element_spec,
loss=tf.keras.losses.SparseCategoricalCrossentropy(),
metrics=[tf.keras.metrics.SparseCategoricalAccuracy()]
)
I have a dataset with numeric features and labels. I am building a federated learning model using TensorFlow (TFF).
Basically, the model that I have is the (neural network) which is always explained in the TFF tutorials.
I want to ask if there is a chance to build another model for the local clients, such as SVM? since it suits my dataset.
My neural network:
def create_keras_model():
initializer = tf.keras.initializers.Zeros()
return tf.keras.models.Sequential([
tf.keras.layers.Input(shape=(18,)),
tf.keras.layers.Dense(128),
tf.keras.layers.Dense(4, kernel_initializer= initializer),
tf.keras.layers.Softmax(),
])
def model_fn():
keras_model = create_keras_model()
return tff.learning.from_keras_model(
keras_model,
input_spec=train_data[0].element_spec,
loss=tf.keras.losses.SparseCategoricalCrossentropy(),
metrics=[tf.keras.metrics.SparseCategoricalAccuracy()]
)
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TFF支持多种模型，包括几乎所有您可以在
tf.keras中编写的模型。您还可以通过子类别来直接创建一个TFF模型， https：https：// wwwwwww。 tensorflow.org/federated/api_docs/python/tff/learning/model 带有前向通过的代码。如果您对一种更有功能的方法感兴趣，也可以通过TFF的FunctionalModel
TFF supports a wide variety of models, including just about any model you can write in
tf.keras.You can also create a TFF model directly by subclassing https://www.tensorflow.org/federated/api_docs/python/tff/learning/Model with the code for your forward pass. If you are interested in a more functional approach, you could also define an SVM model via TFF's FunctionalModel https://www.tensorflow.org/federated/api_docs/python/tff/learning/models/FunctionalModel.