[BUG] The change points detected are different from the points reported from MOA, using the same example

[denisesato]

Describe the bug
I have a sample stream containing durations (in seconds), and I have analyzed the change points using the ADWINChangeDetector class from MOA. The reported change points are 352, 480. When I apply the same analysis using ADWIN class from scikit-multiflow I have got different points: 416, 448, 480.

To Reproduce
I have simulated the problem by comparing the results obtained from MOA and the python library. I have attached the sample file I have applied (the same data is inputted from both) and a sample code.

ADWINPython_Simulate.zip
MOA_Simulate.zip

Expected behavior
I expected the same chance points (352, 480).

Screenshots
If applicable, add screenshots to help explain your problem.

Additional context
I have already identified the difference in the code from scikit-multiflow and I am creating a pull request for it. There are two problems:

1. The method detected_change is not iterating over the complete bucket because of line 317:
   for k in range(cursor.bucket_size_row - 1):

It should work as the Java implementation, to fix:
for k in range(cursor.bucket_size_row):

2. After detecting a change point, the detector should be reset. For fixing this I have added the following lines at the beginning of the add_element method:
   if self.in_concept_change: self.reset()

[denisesato]

If I change the method as I have described the unity test starts to fail, so I did not make the pull request. Could someone help me with this? I have followed the code from MOA sources to implement the changes.