mi-csp-3 number of features
Posted: Fri Apr 08, 2022 3:36 pm
Hello everyone,
I have a question regarding the feature extraction in mi-csp-3-classifier-trainer.xml scenario.
Consider the following diagram:
..................................................................................40 trials
................................................................................. /.........\
.................20 (right) epochs and each epoch has a duration of 4s...........20 (left) epochs and each epoch has a duration of 4s.
......................................................................................|
......................................................................................v
................................................. split the 4sec signals to chunks of duration = 1 sec for each 1/16 of second.
................................................. since 1 sec has 16 chunks => 4 sec -> 64 chunks (for 1 epoch)
................................................. since 1 epoch has 64 chunks => 20 epochs have 1280 chunks
................................................. so each feature aggregator box constructs a feature vector with 1280 features
................................................. and therefore, classifier trainer box gets as input 2 feature vectors with each one having a size of 1280
Why when we execute this scenario, we get on the console that we have 1080 feature vector(s) for input 1 and 1080 feature vector(s) for input 2?
I would appreciate your help.
Thankyou,
Sophia
I have a question regarding the feature extraction in mi-csp-3-classifier-trainer.xml scenario.
Consider the following diagram:
..................................................................................40 trials
................................................................................. /.........\
.................20 (right) epochs and each epoch has a duration of 4s...........20 (left) epochs and each epoch has a duration of 4s.
......................................................................................|
......................................................................................v
................................................. split the 4sec signals to chunks of duration = 1 sec for each 1/16 of second.
................................................. since 1 sec has 16 chunks => 4 sec -> 64 chunks (for 1 epoch)
................................................. since 1 epoch has 64 chunks => 20 epochs have 1280 chunks
................................................. so each feature aggregator box constructs a feature vector with 1280 features
................................................. and therefore, classifier trainer box gets as input 2 feature vectors with each one having a size of 1280
Why when we execute this scenario, we get on the console that we have 1080 feature vector(s) for input 1 and 1080 feature vector(s) for input 2?
I would appreciate your help.
Thankyou,
Sophia