diff --git a/graphsage/minibatch.py b/graphsage/minibatch.py
index 1f53784..0a1cd96 100644
--- a/graphsage/minibatch.py
+++ b/graphsage/minibatch.py
@@ -108,7 +108,7 @@ class EdgeMinibatchIterator(object):
         return adj
 
     def end(self):
-        return self.batch_num * self.batch_size > len(self.train_edges) - self.batch_size + 1
+        return self.batch_num * self.batch_size >= len(self.train_edges)
 
     def batch_feed_dict(self, batch_edges):
         batch1 = []
@@ -125,9 +125,10 @@ class EdgeMinibatchIterator(object):
         return feed_dict
 
     def next_minibatch_feed_dict(self):
-        start = self.batch_num * self.batch_size
+        start_idx = self.batch_num * self.batch_size
         self.batch_num += 1
-        batch_edges = self.train_edges[start : start + self.batch_size]
+        end_idx = min(start_idx + self.batch_size, len(self.train_edges))
+        batch_edges = self.train_edges[start_idx : end_idx]
         return self.batch_feed_dict(batch_edges)
 
     def num_training_batches(self):
@@ -258,7 +259,7 @@ class NodeMinibatchIterator(object):
         return adj
 
     def end(self):
-        return self.batch_num * self.batch_size > len(self.train_nodes) - self.batch_size 
+        return self.batch_num * self.batch_size >= len(self.train_nodes)
 
     def batch_feed_dict(self, batch_nodes, val=False):
         batch1id = batch_nodes
@@ -299,9 +300,10 @@ class NodeMinibatchIterator(object):
         return len(self.train_nodes) // self.batch_size + 1
 
     def next_minibatch_feed_dict(self):
-        start = self.batch_num * self.batch_size
+        start_idx = self.batch_num * self.batch_size
         self.batch_num += 1
-        batch_nodes = self.train_nodes[start : start + self.batch_size]
+        end_idx = min(start_idx + self.batch_size, len(self.train_nodes))
+        batch_nodes = self.train_nodes[start_idx : end_idx]
         return self.batch_feed_dict(batch_nodes)
 
     def incremental_embed_feed_dict(self, size, iter_num):