Performance for converting transactions to BitMatrix

[tonyabracadabra]

I am not familiar with BitMatrix that is used in this library, if I want to pass a list of transactions from python with PyO3, would there be too much overhead converting transactions in form of Vec<Vec<i64>> to the BitMatrix since I have to set those values one by one.

[gahag]

Considering the overhead of itemset mining itself, I would guess that the conversion overhead would be negligible. But I wonder why you are using i64. Is it a requirement for the Python FFI, or are you leveraging other values than 0 and 1?

[tonyabracadabra]

Considering the overhead of itemset mining itself, I would guess that the conversion overhead would be negligible. But I wonder why you are using i64. Is it a requirement for the Python FFI, or are you leveraging other values than 0 and 1?

Ah the input I intend to pass from Python was like
[[0, 10, 23], [22, 23, 55, 289], [2, 55, 999, 777, 4], [0, 22]] where each item in the list is a transaction with number being the feature id

[gahag]

Okay, so for each feature id in your transaction, you will have to set bitmatrix[transaciton_id][feature_id] to true. Please, let me know if this works for you.

[tonyabracadabra]

Okay, so for each feature id in your transaction, you will have to set bitmatrix[transaciton_id][feature_id] to true. Please, let me know if this works for you.

Thanks! May I ask why are you implementing the test dataset instead of using BitMatrix? Could you update a version using BitMatrix for testing as I assume this will be recommended in production?

[gahag]

The test dataset is for test purposes, not a documentation for client users. Even tho, there is a comment there already mentioning one should use a bitmatrix in a production scenario.