On Fri, Feb 12, 2010 at 4:27 AM, Robin Anil <[email protected]> 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. k-means(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
