Talk:Confusion matrix

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Normalization

Normalization of confusion matrix should also be explained. — Preceding unsigned comment added by Scls19fr (talk • contribs) 12:52, 26 April 2015 (UTC)[reply]

Accuracy

We badly need clarification for the definition of producer's and user's accuracy, which is closely associated with the confusion matrix. Comment added by Ctzcheng (talk • contribs) 17:26, 10 March 2008 (UTC)[reply]

Readability

The line "Each column of the matrix represents the instances in a predicted class" does not correspond with the figures which seem to have the True Classes in rows and the Predicted Classes in columns. This seems a bit misleading.. —Preceding unsigned comment added by 128.40.231.243 (talk) 12:15, 1 July 2009 (UTC)[reply]

The many colors in the contingency matrix are very distracting. ("Tables in crazy colours are hard to read."^[1] Formatting of the table should be simplified so that the 4 cells in the intersection of "True Condition" and "Predicted Condition" are prevalent and stand out from the adjunct information in the other cells, specifically those with the formulas. Reduce or eliminate the multiple colors. AEnw (talk) 08:18, 27 December 2015 (UTC)Aenw[reply]

References

^ "Help:Introduction to tables with Wiki Markup/5:Advanced Formatting". Wikipedia Help.

Merger

I suggest this article should be merged at this address with Table of confusion. The issue is the same and there should be only one article in order to avoid confusion //end of lame joke//. --Ben ^T/_C 15:46, 21 May 2007 (UTC)[reply]

I don not support this change of name. "Confusion matrix" has been used for ever in Speech Recognition, and in some other Pattern Recognition tasks, although I cannot trace the ancestry of the use. For instance, some fairly standard sequence recognition toolkits like HTK have tools specifically designed to obtain this "confusion matrix".

I do grant you that most of the times what we see is a table (specially if reading it from paper), and I guess that the "table of confusion" stuff comes from statistics and people who developed their field before computers even existed.

In communications we call a related diagram a ROC (Receiver_operating_characteristic), each of whose working points is a table of confusion. I suggest "table of confusion" goes in there and "confusion matrix" is improved. --FJValverde 09:24, 14 June 2007 (UTC)[reply]

Idea is to have as much information access for as wide an audience as possible here. Since the 2 are the same thing with different terms - what makes sense is merging while redirecting searches for either to this one page. -user AOberai, 14 aug2007

Geography

Just to futher confuse things, confusion matrices arnt soely used in AI (as this article would suggest). A confusion matric is also used in Earth Observation when validating thematic classifications.

Yes, I believe AI is too narrow in this discussion. I suggest "Pattern Recognition" is the actual context where confusion matrices makes sense. FJValverde 09:01, 14 June 2007 (UTC)[reply]

I think they are used more generally in statistics, be it for pattern recognition or earth observation. --Ben ^T/_C 07:41, 20 June 2007 (UTC)[reply]

Er... In my very limited historical view of either statistics and PR, the latter actually sprung from the former, but has since gained some independence: not all techniques in PR are statistical (or even probabilistic). However, I think that confusion matrix is properly a PR concept in the sense that a n-to-m classifier is a very basic PR task. In this sense earth observation and "thematic classification" (meaning classifying the type of soil & such based on the images taken by satellites, right?) is strictly a type of PR task. --FJValverde 08:47, 22 June 2007 (UTC)[reply]

Missing Labeling of Matrix Columns/Rows

Please add labels to the matrix which ones are the actual values and what are the predicted values. Reading the text it becomes clear, but please take note that the article about Receiver Operating Characteristic links to here and over there the confusion matrix is transposed (but labeled). Stevemiller 04:30, 9 October 2007 (UTC)[reply]

Confusion Matrix is Transposed compared to standard practice

The reference https://link.springer.com/content/pdf/10.1023%2FA%3A1017181826899.pdf (https://doi.org/10.1023/A:1017181826899) from 1998 defines the confusion matrix with rows being ground truth and columns being predicted values. It is confusing that wikipedia uses the opposite convention, both here and in ROC. Matlab also uses the opposite convention. Lenhamey (talk) 02:31, 2 May 2019 (UTC)[reply]

remove paragraph

The paragraph that starts: "When a data set is unbalanced..." should probably be removed. I believe this is more a general property of classification algorithms rather than a property of this visualization technique. BAxelrod (talk) 19:23, 16 May 2011 (UTC)[reply]

Contingency table?

Isn't this the same as Contingency table? I understand that different fields have different jargon, but I still feel that the similarity should be acknowledged. 82.181.42.45 (talk) 18:58, 1 November 2011 (UTC)[reply]

I agree, I just asked the same question here: Talk:Contingency table#Contingency table vs confusion matrix pgr94 (talk) 13:45, 13 June 2013 (UTC)[reply]

I disagree. A confusion matrix can be considered a special kind of contingency table (between real and observed value), but I don't think they should be... confused. -- RFST (talk) 06:31, 28 March 2016 (UTC)[reply]

Mixed conventions

The introduction states that the columns are the predicted class and the rows are the actual class. In the Example section this convention is reversed without acknowledgement. In the Table of confusion section the originally stated convention is used. I propose the introduction note that there are multiple conventions, but then a consistent convention is used within the article. Doug Paul (talk) 04:07, 29 April 2012 (UTC)[reply]

Confusion Table and True Negatives

I would have expected the outcome of the confusion table to have 14 true negatives, because it is stated that these are correctly predicted non cats. So (3 dogs + 11 rabbits) which are correctly predicted non cats. However I can see the argument for just adding all the ((TP+FP+FN) - rest of instances). Because these are animals, that are not fn, fp or tp cats. Do we have some reference to a formula on how TN is defined more precisely?

(Jogoe12 (talk) 18:46, 19 December 2016 (UTC)).[reply]

removed one line of wrong markup at the top

Removed this

   Double left curly bracket   Confusion matrix terms|recall=   Double right curly bracket

from the article today since i have no idea what it is supposed to do, and it results in a mess at the beginning of the article - Right after the title and before 'condition positive(P)' on the page I see this garbage

   "Insert non-formatted text here{| class="wikitable" width=35% style="float:right;font-size:98%; margin-left:0.5em; padding:0.25em; background:#f1f5fc;" |+     
   Terminology and derivations
   from a confusion matrix |- style="vertical-align:top;" |  "  — Preceding unsigned comment added by Thinkadoodle (talk • contribs) 15:06, 8 June 2020 (UTC)[reply]

Can you please undo this change? This table was one of the best reference for the confusion matrix and its derived metrics out there. It used to be in a grey box next to the article. --Marvmind (talk) 21:23, 8 June 2020 (UTC)[reply]

[1] "Help:Introduction to tables with Wiki Markup/5:Advanced Formatting". Wikipedia Help.

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