Latest revision as of 15:07, 19 November 2015

#!PATTERN+

info

Pattern+ is an annotated edition of the webmining module Pattern. The alpha-release of Pattern+ serves two interconnected goals: It is first of all an attempt to grow our understanding of - and concern with - the culture of data-mining, and then to feed this back into the practice of data-mining itself. It is also an experiment with forms of collaborative techno-critique that locate themselves closely to actual software objects. (from: #!PATTERN+.readme)

Contributors are Manetta Berends, Christina Colchoir, Frederic Janssens, Anne Laforet, My Lê, Femke Snelting, Kym Ward.

Relearn

Pattern+ is initiated as a project during the Relearn summerschool 2015 in Brussels, but is also a continuation of the introduction workshop to Pattern, given by from Guy De Pauw during Cqrrelations (Jan. 2015).

material from Relearn 2015

* Knowledge Discovery in Data (KDD) steps
* data mining culture

other resources

* earlier notes (Jul. 2015)
* notes taken during Relearn Aug. 2015, training common sense
* #!PATTERN+.readme

* the Annotator, Cqrrelations Jan. 2015, on etherpad
* notes Cqrrelations day 1, day 2, day 3, day 4, day 5

notes

* problems related to the common-sense results:
- "it is only possible to categorize, after you have defined the categories" — Solon Barocas at Cqrrelations, 2015
- how can we escape the vicious circle (of training by showing examples of current 'status quo')?
- when an algorithm is made to predict a certain 'truth', how does it find the unpredictable / margins?

@@ Line 1: / Line 1: @@
-<div style="width:75%;">
+<div style="width:100%;max-width:850px;">
 __NOTOC__
 =#!PATTERN+=
@@ Line 9: / Line 9: @@
 Contributors are Manetta Berends, Christina Colchoir, Frederic Janssens, Anne Laforet, My Lê, Femke Snelting, Kym Ward.
+==Relearn==
+Pattern+ is initiated as a project during the Relearn summerschool 2015 in Brussels, but is also a continuation of the introduction workshop to Pattern, given by from Guy De Pauw during Cqrrelations (Jan. 2015).
+===material from Relearn 2015===
+[[User:Manetta/meta-mining/knowledge-discovery-in-data|* Knowledge Discovery in Data (KDD) steps]]<br>
+[[User:Manetta/meta-mining/data-mining-culture|* data mining culture]]<br>
+===other resources===
 [http://pad.constantvzw.org/p/commonsense * earlier notes (Jul. 2015)]<br>
 [http://relearn.be/2015/etherdump/training-common-sense.html * notes taken during Relearn Aug. 2015, training common sense]<br>
@@ Line 15: / Line 22: @@
 [http://www.cqrrelations.constantvzw.org/1x0/the-annotator/ * the Annotator, Cqrrelations Jan. 2015], [http://pad.constantvzw.org/p/the_annotator on etherpad]<br>
 [http://annotations.manettaberends.nl/txt/cqrrelations-jan-2015-day-1.html * notes Cqrrelations day 1], [http://annotations.manettaberends.nl/txt/cqrrelations-jan-2015-day-2.html day 2], [http://annotations.manettaberends.nl/txt/cqrrelations-jan-2015-day-3.html day 3], [http://annotations.manettaberends.nl/txt/cqrrelations-jan-2015-day-4.html day 4], [http://annotations.manettaberends.nl/txt/cqrrelations-jan-2015-day-5.html day 5]
 ==notes==
   * problems related to the common-sense results:
-  - "it is only possible to categorise, after you have defined the categories" — Solon Barocas at Cqrrelations, 2015
+  - "it is only possible to categorize, after you have defined the categories" <small>— Solon Barocas at Cqrrelations, 2015</small>
-  - how can we escape the vicious circle  (of training by showing examples of current 'status quo')?
+  - how can we escape the vicious circle (of training by showing examples of current 'status quo')?
   - when an algorithm is made to predict a certain 'truth', how does it find the unpredictable / margins?
 ==related==
+[http://relearn.be/2015/ * Relearn website]<br>
 [http://www.clips.ua.ac.be/pages/pattern * CLiPS Pattern, official website]<br>