<commit_before>HTK - Hidden Markov Model Toolkit (HTK) [for speech recognition/synthesis, handwriting, and DNA sequencing] http://htk.eng.cam.ac.uk/
HMM for Matlab - http://www.cs.ubc.ca/~murphyk/Software/HMM/hmm.html + literature

== HMM todo ==
- change per-student effects to resemble Logistic Regression: student pLo and pT
    are NOT correction to skill's pLo and pT, but true student intercept and 
    slope emulators
- add per-item (problem) effects
- Collapse all gradient descent to one class with "switchers" for per-student and
    per-skill attributes
- step tolerance == convergence tolerance, BEWARE! when conv tolerance grows
- check whether AIC and BIC computed correctly (n.parameters in particular)
- add capability to run multiple model fits on one input file read (e.g., via a
    -F <filename> parameters where file contains multiple modeling specs
- (?) striped data  - destructive read, if beyond certain border, delete previous

- <NAME> - does not have fitting of as one skill first
- <NAME> - does not have selective fitting of PI,A,B
- All other steppers/fitters (<NAME>, LevinsonRabiner, Exponentiated etc.) are not updated properly.

== Assumptions ==
- columns: observation, user, step, skill[, time in ms]


== GGordon ==GraphLab Carlos CS CMU - parallel
- Tinkerers, less flex than R bit more
- DataShop access to data
- potential clients: Ken, John, Phil, Emma, 
- git hub, sourceforge - repositories, search there
- Uncertainty in AI mail list

<commit_msg>update todo<commit_after>HTK - Hidden Markov Model Toolkit (HTK) [for speech recognition/synthesis, handwriting, and DNA sequencing] http://htk.eng.cam.ac.uk/
HMM for Matlab - http://www.cs.ubc.ca/~murphyk/Software/HMM/hmm.html + literature

== HMM todo ==
- change per-student effects to resemble Logistic Regression: student pLo and pT
    are NOT correction to skill's pLo and pT, but true student intercept and 
    slope emulators
- add per-item (problem) effects
- Collapse all gradient descent to one class with "switchers" for per-student and
    per-skill attributes
- step tolerance == convergence tolerance, BEWARE! when conv tolerance grows
- check whether AIC and BIC computed correctly (n.parameters in particular)
- add capability to run multiple model fits on one input file read (e.g., via a
    -F <filename> parameters where file contains multiple modeling specs
- (?) striped data  - destructive read, if beyond certain border, delete previous

- <NAME> - does not have fitting of as one skill first
- <NAME> - does not have selective fitting of PI,A,B
- All other steppers/fitters (<NAME>, LevinsonRabiner, Exponentiated etc.) are not updated properly.

== Assumptions ==
- columns: observation, user, step, skill[, time in ms]


== GGordon ==GraphLab Carlos CS CMU - parallel
- Tinkerers, less flex than R bit more
- DataShop access to data
- potential clients: Ken, John, Phil, Emma, 
- git hub, sourceforge - repositories, search there
- Uncertainty in AI mail list

== commandline commits/push ==
push: git push dropbox master




{'fraction_non_alphanumeric': 0.08464566929133858, 'fraction_numerical': 0.0, 'mean_word_length': 3.990180032733224, 'pattern_counts': {'":': 0, '<': 11, '<?xml version=': 0, '>': 11, 'https://': 0, 'lorem ipsum': 0, 'www.': 2, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '6549634', 'n_tokens_mistral': 894, 'n_tokens_neox': 837, 'n_words': 388}