Open dhimmel opened 8 years ago
Tagging everyone who said they were interested in contributing to the machine learning part of the project in the introduction thread: @htcai, @loucru1 @bmcgeehan @umeshiso @swbiggs4 @danrieman @rramyr @Inquisitive-Geek @brankaj @yl565 @Ramaa-Nathan @ejsegall @FadiAlnabolsi @sameertipnis @VijYadav @ctipnis.
Update: also tagging @yigalron.
Thanks for the sample notebook! I would like to implement Linear SVM with regularization.
@htcai awesome. Can you specify which sklearn function(s) you plan to use for the model?
Thanks for setting this up. I would like to try LASSO, implementation sklearn.linear_model.LassoCV.
I consulted the chart posted by @yl565 . I plan to try sklearn.svm.LinearSVC.
I plan to implement the Nearest Neighbors Classification
@yigalron did you want to claim KNeighborsClassifier
, RadiusNeighborsClassifier
, or both?
I'm planning to start with the KNeighborsClassifier
I plan to test Decision Tree CART (sklearn.tree.DecisionTreeClassifier) algorithm
Hi Daniel, Is there "algorithms" directory created already? I I can't see it. Sorry, I am still learning about Github.
@VijYadav, you'll have to create the directory, since it currently doesn't exist. I'll submit a pull request as an example.
when trying to set up the conda environment on windows (conda env create --quiet --force --file environment.yml) I get an error:
yaml.scanner.ScannerError: mapping values are not allowed here
in "
any ideas what I did wrong?
@yigalron can you file a new issue or comment on #15 with the conda installation issue? It's best to keep issues focused and uncluttered.
OK; anyway it seems to have been a user error; I'm trying again
Hi all, I will claim AdaBoost.
Hey Folks - I will give RandomForestClassifier a shot. Mans
I have an initial version of the K-Nearest neighbor algorithm, and I issued a pull request; not sure if it got into the master. I won't be able to join the next meeting, but will continue to work on this remotely.
I would like to claim spectral clustering, and give it a try
I would like to work on the multi-layer perceptron classifier.
sklearn.neural_network.MLPClassifier
I'd like to claim LDA/QDA and give it a shot
I'll also take a look at the Passive Aggressive Classifier
In the August 26 meetup, we discussed having each team member in the machine learning group claim an algorithm. We've made lot's of progress on the example notebook (
1.TCGA-MLexample.ipynb
) since then (see #18 & #25). Currently,1.TCGA-MLexample.ipynb
uses elastic net logistic regression implemented inSGDClassifier
.The goal of this repository is for people to:
1.TCGA-MLexample.ipynb
in analgorithms
directory. So if I took the SVM classifier, I would copy1.TCGA-MLexample.ipynb
toalgorithms/SVC-dhimmel.ipynb
. Then I would make my edits toalgorithms/SVC-dhimmel.ipynb
to switch to an SVC classifier.Best of luck! If you can work on this before the August 9 meetup then great! Otherwise make sure to bring a laptop with the
cognoma-machine-learning
environment installed.