2
votes
Machine Learning Models for Longitudinal Data
I added "longitudinal variables" that take into account the number of times the students took the test and their most recent average cumulative score:
My Question:
a. Does the approach that ...
- 101
2
votes
Distinguishing text with opposite meanings in SVM (False Information Detection)
Going step by step:
Preprocessing
Preprocessing is a big deal in NLP, out there you'll find many tutorials describing the classic steps but few explanations about why and when you should actually ...
- 4,283
2
votes
Identify features don't hold required information in a ML problem
To test hypothesis 1 the only way is to try different architectures and/or approaches. Basically brutal grid search.
To test hypothesis 2 the way to go is data exploration and feature importance ...
- 4,283
1
vote
Machine Learning Models for Longitudinal Data
I think there are some things you can do to get it work better.
Suggestions:
add a column to the input giving number of previous tries at the test. If there was a score to go with it, include the ...
- 251
1
vote
Which models can I use for supervised learning with images?
Papers With Code have a great summary of the tasks in computer vision and their respective State of the Art models. Also the tasks page from HuggingFace serves as a great reference.
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