IndexError: index 15 is out of bounds for axis 1 with size 15

[onlyff]

hi，there are some errors when I run the code.
First, I exact features and get the comprehensive feature set(16 features):{'Connect_After': 5, 'Connect_Normal': 4, 'Connect_Weekend': 6, 'Disconnect': 7, 'Email_In': 9, 'Email_Out': 10, 'File_doc': 15, 'File_exe': 11, 'File_jpg': 12, 'File_txt': 14, 'File_zip': 13, 'Logoff': 3, 'Website': 8,
'Weekday_Logon_After': 1, 'Weekday_Logon_Normal': 0, 'Weekend_Logon': 2}, write "r42_features_complex.h5" to the disk.
Then I run "R4 Processing", when user_id is NGF0157, the user has 15 features, when compute the probability, the error is as follows:

in compute_probs(user_df)
37
38 print("timesTrained:",timesTrained)
---> 39 model.learn(seq, max_iters=20, threshold=0.01, restart_threshold=0.1,max_restarts=5, inertia=0.5)
40 timesTrained+=1
41

~\InsiderThreatDetection-master\HiddenMarkovModel\HiddenMarkovModel.py in learn(self, seq, max_iters, threshold, restart_threshold, max_restarts, inertia)
118 while(not done):
119
--> 120 forward_matrix, scaling_factors, log_prob = self.forward(seq, start = starts, trans=transitions, emiss= emissions)
121
122 backward_matrix = self.backward(seq, scaling_factors, start = starts, trans=transitions, emiss= emissions)

~\InsiderThreatDetection-master\HiddenMarkovModel\HiddenMarkovModel.py in forward(self, seq, start, trans, emiss)
45 for symbol_index, symbol in enumerate(seq[1:], start=1):
46
---> 47 forward_matrix[:,symbol_index] = emissions[:,symbol] * np.dot(forward_matrix[:,symbol_index-1], transitions)
48
49 # Normalise forward matrix

IndexError: index 15 is out of bounds for axis 1 with size 15

As we know, not every user has 16 features, how tore solve the problem when training HMM model? Thanks a lot!