Spaces:
Running
Running
File size: 1,203 Bytes
92c34be |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 |
import tensorflow as tf
from tensorflow.keras import layers, models
class AnomalyDetectionModel:
def __init__(self, input_shape):
self.model = self.build_model(input_shape)
def build_model(self, input_shape):
model = models.Sequential([
layers.Dense(64, activation='relu', input_shape=(input_shape,)),
layers.Dense(32, activation='relu'),
layers.Dense(16, activation='relu'),
layers.Dense(1, activation='sigmoid')
])
model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])
return model
def train(self, X_train, y_train, epochs=10, batch_size=32, validation_split=0.2):
history = self.model.fit(X_train, y_train, epochs=epochs, batch_size=batch_size, validation_split=validation_split)
return history
def evaluate(self, X_test, y_test):
loss, accuracy = self.model.evaluate(X_test, y_test)
return loss, accuracy
# Example usage:
# anomaly_model = AnomalyDetectionModel(X_train.shape[1])
# history = anomaly_model.train(X_train, y_train)
# loss, accuracy = anomaly_model.evaluate(X_test, y_test)
# print(f'Test Accuracy: {accuracy:.4f}')
|