def rebalance(self):
from plastk import rand
data = rand.shuffle(self.all())
self._flat = FlatVectorDB(vector_len = self.vector_len)
self._flat.db = data
self._le = self._gt = None
self._split()
def learn_batch(self, data):
"""
Learns on a batch of data, given as a sequence. The batch is shuffled,
then presented sequentially to self.learn_step()
"""
import plastk.rand
self.verbose("Training on", len(data), "examples.")
for i in xrange(self.batch_epochs):
data = rand.shuffle(data)
for X, Y in data:
self.learn_step(X, Y)
def learn_batch(self,data):
"""
Learns on a batch of data, given as a sequence. The batch is shuffled,
then presented sequentially to self.learn_step()
"""
import plastk.rand
self.verbose("Training on",len(data),"examples.")
for i in xrange(self.batch_epochs):
data = rand.shuffle(data)
for X,Y in data:
self.learn_step(X,Y)
