I’m going to sketch out the next few things to plan and code for the DSL library. I have so far provided the ability to describe the network but I haven’t yet provided a way to describe the distributions. For … Continue reading
> import Data.Ord (comparing) This is completely random but I thought it was a neat use of laziness. You are familiar with lexicographical ordering? Haskell’s compare of lists implements this. ghci> [1,2] < [1,3] True ghci> [1,3,4] < [1,3,4,5] True … Continue reading
I want to start another aside because this is something I spend a significant amount of time thinking about. That is, how do you learn a new language when you are approaching 30? Living in India, I think it’s a … Continue reading
I’ve now cleaned up (in befb0f3cca0c212e368497e86f030aa96355be18) the Reader and Writer interfaces and added it to Statistics.GModeling.Gibbs. I’ve removed references to Support and simply parameterized using a key type k and value type v. > data Reader k v = Reader … Continue reading
I am putting together what I have so far in a repository here. So far, (133e22dc979d988706aafe52a346cee004f70ca5) it contains Statistics.GModeling.DSL Statistics.GModeling.Models.HMM Statistics.GModeling.Models.LDA Statistics.GModeling.Models.FixedTreeLDA Will continue building the pieces in upcoming posts.
I think most have heard something like you only need suprisingly few people in a room before two people in the room end up sharing a birthday. But I never bothered to work it out. Let me do that. First, … Continue reading
A quick aside. I was thinking about how response variables are attached to generative models. For instance, if we want to say have binary classification on documents we would normally 1) take the dot product the topic vector with a … Continue reading