"""
Tensorflow Implementation for Improved Deep Embedded Clustering FcIDEC and FcIDEC-DA:
- Xifeng Guo, Long Gao, Xinwang Liu, Jianping Yin. Improved Deep Embedded Clustering with Local Structure Preservation. IJCAI 2017.
- Xifeng Guo, En Zhu, Xinwang Liu, and Jianping Yin. Deep Embedded Clustering with Data Augmentation. ACML 2018.
Author:
Xifeng Guo. 2018.6.30
"""
from tensorflow.keras.models import Model
from FcDEC import FcDEC
class FcIDEC(FcDEC):
def __init__(self, dims, n_clusters=10, alpha=1.0):
super(FcIDEC, self).__init__(dims, n_clusters, alpha)
self.model = Model(inputs=self.autoencoder.input,
outputs=[self.model.output, self.autoencoder.output])
def predict(self, x): # predict cluster labels using the output of clustering layer
q = self.model.predict(x, verbose=0)[0]
return q
def compile(self, optimizer='sgd', loss=['kld', 'mse'], loss_weights=[0.1, 1.0]):
self.model.compile(optimizer=optimizer, loss=loss, loss_weights=loss_weights)
def train_on_batch(self, x, y, sample_weight=None):
return self.model.train_on_batch(x, [y, x], sample_weight)[0]
