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Machine Learning for kdb+/q
Examples
Reinforcement Learning
DBSCAN
Find clusters of points based on density
q)t:{3?1.} each til 100
q)dbscan[t;3;.2]
-1 0 0 1 0 -1 0 -1 1 1 2 0 3 0 -1 1 4 1 1 1 2 1 0 -1 2 1 2 1 1 4 1 4 1 1 1 0 ..
k nearest neighbors
Find the n closest points to a target
q)t:(`a`b`c!) each {3?100} each til 1000000
q)knn[t;`a`b`c!1 2 3;3]
a b c dist
----------
1 2 3 0
1 2 4 1
0 2 3 1
k-means clustering
Find n centroids in a dataset partitioned by k-means
q)iris:flip `sl`sw`pl`pw`class!("FFFFS";",") 0: `:iris.csv
q)kmeans[delete class from iris;3]
sl sw pl pw
-----------------------------------
6.85 3.073684 5.742105 2.071053
5.901613 2.748387 4.393548 1.433871
5.006 3.418 1.464 0.244
Iris Dataset available here: https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data
Decision Tree (ID3)
q)id3[weatherdata[]]
n_ v_ class
-------------------------------------
,`outlook ,`overcast yes
`outlook`wind `rain`weak yes
`outlook`wind `rain`strong no
`outlook`humidity `sunny`high no
`outlook`humidity `sunny`normal yes