This is starting to experiment with the UCI record linkage comparison data.
contact: fettermania@gmail.com
- TODO:
- Put data itself in github?
- Cache results of reading files in.
- Figure out missing edge weight strategy (steal from ds-exp/clustering)
- Start basic machine learning
- Snag the data set from https://archive.ics.uci.edu/ml/datasets/Record+Linkage+Comparison+Patterns
- Extract all block_1.csv through block_10.csv and move under "resources/uci/"
In REPL, require the namespace:
(require '[uci-test.core :as uci]
'[ubergraph.core :as uber])
Visualize very small subgraph, nodes 99 and below. Note, every call to evaluate-uci-data takes a while to read in all files (TODO cache):
(def mygraph (uci/evaluate-uci-data))
(uber/viz-graph mygraph {:auto-label true})
Get stats on a much bigger subgraph.
(def mygraph (uci/evaluate-uci-data "uci/block_" 10 10000 true))
- Arguments are:
- file prefix under resource directory (defaults to recommended above)
- file count (counts 1 to 10 by default)
- max node id to include in subgraph (max of 99999 kills memory)
- whether to "save-memory?" by ditching edge attributes (features and "prob connected")
Copyright © 2016 FIXME
Distributed under the Eclipse Public License either version 1.0 or (at your option) any later version.