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GitHub / jolars/linum issues and pull requests
#22 - Add code style reference.
Issue -
State: closed - Opened by jolars almost 7 years ago
#22 - Add code style reference.
Issue -
State: closed - Opened by jolars almost 7 years ago
#21 - 90% code coverage is a nice goal.
Issue -
State: closed - Opened by jolars almost 7 years ago
#21 - 90% code coverage is a nice goal.
Issue -
State: closed - Opened by jolars almost 7 years ago
#20 - if you want to stick to S4 please clarify
Issue -
State: closed - Opened by jolars almost 7 years ago
- 1 comment
#20 - if you want to stick to S4 please clarify
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State: closed - Opened by jolars almost 7 years ago
- 1 comment
#19 - if I understand correctly saga_train does CV
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State: closed - Opened by jolars almost 7 years ago
- 1 comment
#19 - if I understand correctly saga_train does CV
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State: closed - Opened by jolars almost 7 years ago
- 1 comment
#18 - Section 10. The link should be to table 3, not section 10.
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State: closed - Opened by jolars almost 7 years ago
#17 - about the data set to be included in the package, I would recommend looking at the SAGA paper and using one/seveeral of those (maybe it is alreayd in scikit-learrn?)
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State: closed - Opened by jolars almost 7 years ago
#16 - In timeline that is good to mention that you will drop the CV features
Issue -
State: closed - Opened by jolars almost 7 years ago
#15 - Under management of coding project you can delete "doxygen/roxygen" and instead write "roxygen2" which I think is the current de factor standard.
Issue -
State: closed - Opened by jolars almost 7 years ago
#14 - You write "compare the performance" but I would recommend to be even more specific -- in terms of objective function values versus iterations, in terms of wall time? etc
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State: closed - Opened by jolars almost 7 years ago
#13 - You need to motivate the problem space more. Say a bit more about
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State: closed - Opened by jolars almost 7 years ago
#12 - You should cite existing literature more thoroughly on this: off
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State: closed - Opened by jolars almost 7 years ago
#11 - Be clearer about exactly which features you intend to match from
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State: closed - Opened by jolars almost 7 years ago
#10 - You never actually say what "SAGA" stands for.
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State: closed - Opened by jolars almost 7 years ago
- 1 comment
#9 - glmnet uses screening rules (e.g., Tibshirani et al. JRSSB 2012) to
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State: closed - Opened by jolars almost 7 years ago
#8 - I'd compare (featurewise) to the SKLearn implementation. If you're
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State: closed - Opened by jolars almost 7 years ago
#7 - Section 2: "interest _in_ XXX"; "My firstmost interests lie in" ==>
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State: closed - Opened by jolars almost 7 years ago
#6 - Section 4: list what graduate degree you are working towards + what
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State: closed - Opened by jolars almost 7 years ago
#5 - Table 2: I don't consider plots of regularization paths to be
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State: closed - Opened by jolars almost 7 years ago
#4 - Section 7: much more needed here, but what you have is too
Issue -
State: closed - Opened by jolars almost 7 years ago
#3 - Table 3
Issue -
State: closed - Opened by jolars almost 7 years ago
#2 - Få output för electrotest och exemplet att matcha
Pull Request -
State: closed - Opened by ArvinJA almost 7 years ago
- 2 comments
#1 - Electrotest johan
Pull Request -
State: closed - Opened by jolars almost 7 years ago
- 3 comments