ans92
commented
3 years ago I have used data set of 20000 rows and my issue resolved. I was first trying to do it on smaller data set. Do not know what is reason behind it.
Closed ans92 closed 3 years ago
ans92
commented
3 years ago I have used data set of 20000 rows and my issue resolved. I was first trying to do it on smaller data set. Do not know what is reason behind it.
Hi, First of all, I want to say thanks for this very helpful code. I am a beginner and we are tried to reproduce the results of this experiment. I am trying to running this code on google colab. Due to resources limit I shorten the data set to first 200 rows. I write following lines to run this code files in google colab:
!python3 /content/drive/MyDrive/IRTM_Term_Project_Sem_1/short_text_cnn_cluster-master/utils.py .!python3 /content/drive/MyDrive/IRTM_Term_Project_Sem_1/short_text_cnn_cluster-master/train_cnn.py .When I run second command then I am getting these errors. Please help me how can I remove those errors:
/usr/local/lib/python3.6/dist-packages/sklearn/cluster/_kmeans.py:88: RuntimeWarning: divide by zero encountered in log n_local_trials = 2 + int(np.log(n_clusters)) /usr/local/lib/python3.6/dist-packages/sklearn/cluster/_kmeans.py:88: RuntimeWarning: divide by zero encountered in log n_local_trials = 2 + int(np.log(n_clusters)) /usr/local/lib/python3.6/dist-packages/sklearn/cluster/_kmeans.py:88: RuntimeWarning: divide by zero encountered in log n_local_trials = 2 + int(np.log(n_clusters)) joblib.externals.loky.process_executor._RemoteTraceback: """ Traceback (most recent call last): File "/usr/local/lib/python3.6/dist-packages/joblib/externals/loky/process_executor.py", line 431, in _process_worker r = call_item() File "/usr/local/lib/python3.6/dist-packages/joblib/externals/loky/process_executor.py", line 285, in call return self.fn(*self.args, *self.kwargs) File "/usr/local/lib/python3.6/dist-packages/joblib/_parallel_backends.py", line 595, in call return self.func(args, **kwargs) File "/usr/local/lib/python3.6/dist-packages/joblib/parallel.py", line 263, in call for func, args, kwargs in self.items] File "/usr/local/lib/python3.6/dist-packages/joblib/parallel.py", line 263, in
for func, args, kwargs in self.items]
File "/usr/local/lib/python3.6/dist-packages/sklearn/cluster/_kmeans.py", line 314, in _kmeans_single_elkan
x_squared_norms=x_squared_norms)
File "/usr/local/lib/python3.6/dist-packages/sklearn/cluster/_kmeans.py", line 626, in _init_centroids
x_squared_norms=x_squared_norms)
File "/usr/local/lib/python3.6/dist-packages/sklearn/cluster/_kmeans.py", line 88, in _k_init
n_local_trials = 2 + int(np.log(n_clusters))
OverflowError: cannot convert float infinity to integer
"""
The above exception was the direct cause of the following exception:
Traceback (most recent call last): File "/content/drive/MyDrive/IRTM_Term_Project_Sem_1/short_text_cnn_cluster-master/train_cnn.py", line 157, in
km.fit(V)
File "/usr/local/lib/python3.6/dist-packages/sklearn/cluster/_kmeans.py", line 956, in fit
for seed in seeds)
File "/usr/local/lib/python3.6/dist-packages/joblib/parallel.py", line 1054, in call
self.retrieve()
File "/usr/local/lib/python3.6/dist-packages/joblib/parallel.py", line 933, in retrieve
self._output.extend(job.get(timeout=self.timeout))
File "/usr/local/lib/python3.6/dist-packages/joblib/_parallel_backends.py", line 542, in wrap_future_result
return future.result(timeout=timeout)
File "/usr/lib/python3.6/concurrent/futures/_base.py", line 432, in result
return self.get_result()
File "/usr/lib/python3.6/concurrent/futures/_base.py", line 384, in get_result
raise self._exception
OverflowError: cannot convert float infinity to integer