On Fri, Feb 12, 2010 at 4:27 AM, Robin Anil <robin.anil@gmail.com> wrote:
> 1. Locally Weighted Linear Regression
>
Not sure how important this one is.
> 2. Naive Bayes(We have this and CBayes as a bonus)
> 3. Gaussian Discriminative Analysis (GDA)
>
DP clustering does this, effectively, I think.
> 4. Logistic Regression (LR) (In development)
>
SGD. In dev as you say.
> 5. kmeans(we have this and kmeans++ is in development)
> 6. Neural Network (NN)
>
SGD could implement this if we like. Not sure that we need M/R to get speed
here.
> 7. Principal Components Analysis (PCA)
>
= SVD and Jake's contribution.
> 8. Independent Component Analysis (ICA)
> 9. Expectation Maximization (EM) (We have it in pig script and in couple
> of algorithms not generic yet)
>
DP clustering is a version of this for some applications.
> 10. Support Vector Machine (SVM)(In development  The pegasus version)
>
So I think that we are actually at about 7 or 8 / 10 with several
interesting additions.
More than the original 10, we need realistic and simple examples.

Ted Dunning, CTO
DeepDyve
