Precision and Recall
In pattern recognition and information retrieval, precision (also called positive predictive value) is the fraction of retrieved instances that are relevant, while recall (also known as sensitivity) is the fraction of relevant instances that are retrieved. Both precision and recall are therefore based on an understanding and measure of relevance. Suppose a program for recognizing dogs in scenes from a video identifies 7 dogs in a scene containing 9 dogs and some cats. If 4 of the identifications are correct, but 3 are actually cats, the program's precision is 4/7 while its recall is 4/9. When a search engine returns 30 pages only 20 of which were relevant while failing to return 40 additional relevant pages, its precision is 20/30 = 2/3 while its recall is 20/60 = 1/3.
In statistics, if the null hypothesis is that all and only the relevant items are retrieved, absence of type I and type II errors corresponds respectively to maximum precision (no false positives) and maximum recall (no false negatives). The above pattern recognition example contained 7 − 4 = 3 type I errors and 9 − 4 = 5 type II errors. Precision can be seen as a measure of exactness or quality, whereas recall is a measure of completeness or quantity.
In simple terms, high recall means that an algorithm returned most of the relevant results, while high precision means that an algorithm returned substantially more relevant results than irrelevant.

This is an excerpt from the article Precision and Recall from the Wikipedia free encyclopedia. A list of authors is available at Wikipedia.
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Recall and Precision
Precision and Recall are the basic measures used in evaluating search strategies. As shown in the first two figures on the left, these measures assume: There is a ...
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Precision and recall - Wikipedia, the free encyclopedia
In pattern recognition and information retrieval, precision (also called positive predictive value) is the fraction of retrieved instances that are relevant, while recall ...
en.wikipedia.org/wiki/Precision_and_recall
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FAQ: Precision and Recall Calculation - KDnuggets
Calculating Precision and Recall is actually quite easy. Imagine there are 100 positive cases among 10,000 cases. You want to predict which ones are positive, ...
www.kdnuggets.com/faq/precision-recall.html
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What is the difference between Precision and Recall? - BA Insight
Mar 7, 2011 ... Information retrieval experts define relevance as having two components; Precision and Recall In an Enterprise setting it is difficult to achieve ...
www.bainsight.com/blog-archive/Pages/3-7-2011-1.aspx
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ongoing by Tim Bray · On Search: Precision and Recall - tbray.org
Jun 22, 2003 ... Problems · While Precision and Recall are very helpful in talking about how good search systems are, they are nightmarishly difficult to actually ...
www.tbray.org/ongoing/When/200x/2003/06/22/PandR
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Computing Accuracy Precision And Recall - SlideShare
Calculating Accuracy, Precision and Recall PREDICTION.
www.slideshare.net/nicbet/computing-accuracy-precision-and-recall-presentation
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Evaluating a classification model – What does precision and recall ...
http://www.compumine.com/web/public/newsletter/20071/precision-recall. Evaluating a classification model – What does Precision and Recall tell me? Once you ...
www.cs.odu.edu/~mukka/cs495s13/Lecturenotes/Chapter5/recallprecision.pdf
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Precision & Recall tuning - Search Technologies
Precision and Recall tuning is a key part of successful search engine deployments . Search Technologies is the leading IT services company dedicated to search ...
www.searchtechnologies.com/precision-recall.html
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Accuracy and precision - Wikipedia, the…
In the fields of science, engineering, industry, and statistics, the accuracy of a measurement system is the degree of closeness of measurements of a quantity to that ...
en.wikipedia.org/wiki/Accuracy_and_precision
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Information retrieval - Wikipedia, the…
Information retrieval is the activity of obtaining information resources relevant to an information need from a collection of information resources. Searches can be ...
en.wikipedia.org/wiki/Information_retrieval
Search results for "Precision and Recall"
Precision and Recall in science
[PDF]Lecture 13 Evaluation: Precision and Recall - University of Washington
Aug 30, 2012 ... Evaluation: Precision and Recall. University of Washington. Linguistics 473: Computational Linguistics Fundamentals. 1. Thursday, August 30 ...
University of Kashmir Digital Library: Precision and Recall of Five ...
Title: Precision and Recall of Five Search Engines for Retrieval of Scholarly Information in the Field of Biotechnology. Other Titles: WEBOLOGY V2(2) August, ...
[PDF]Comparative Recall and Precision of Simple and Expert Searches in ...
demography librarians at three top universities. For simple searches, Google Scholar's recall and precision are well above average. For expert searches, the ...
[PDF]Precision and Recall of GlOSS Estimators for - Stanford University
Precision and Recall of GlOSS Estimators for Database Discovery. Luis Gravano. H ector Garc a-Molina. Anthony Tomasic. Computer Science Department.
[PDF]Unachievable Region in Precision-Recall Space and Its Effect on ...
University of Wisconsin – Madison, 1300 University Avenue, Madison, WI 53706 USA. Abstract. Precision-recall (PR) curves and the areas under them are ...
Information retrieval - Wikipedia, the free encyclopedia
Many universities and public libraries use IR systems to provide access to books, ... 3.1 Precision; 3.2 Recall; 3.3 Fall-out; 3.4 F-measure; 3.5 Average precision ...
Mining photographic collections to enhance the precision and recall ...
Jun 17, 2013 ... Mining photographic collections to enhance the Precision and Recall of search results using semantically ... PhD thesis, Concordia University.
[PDF]Generative Modeling for Maximizing Precision and Recall in ...
Generative Modeling for Maximizing Precision and Recall in. Information Visualization. Jaakko Peltonen1. Samuel Kaski1,2. 1Aalto University, Department of ...
[PDF]ROC, Precision-Recall, and All That
Prof. William H. Press. Spring Term, 2008. The University of Texas at Austin. Unit 17: Classifier Performance: ROC,. Precision-Recall, and All That ...
Books on the term Precision and Recall
Foundations of Statistical Natural Language Processing
Hinrich Schütze, 1999
INTERPOLATED AVERAGE PRECISION LEVELS OF RECALL INTERPOLATE PRECISION-RECALL CURVES F MEASURE (d4), which averages to 0.5726. If there are other relevant documents further down the list then these also have to be ...
Multimedia Retrieval
H. Henk M. Blanken, Henk Ernst Blok, Arjen P. de Vries, 2007
13.3.4 Combining Precision and Recall: The F-Measure For many glass box evaluations, there is no ranked list that needs to be considered. For instance, a tool that detects video shot boundaries (see Section 13.5.1) does not really rank ...
Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data
Bīng Liú, 2011
100% 90% 80% 40% 50% 60% 70% 30% 20% 0% 10% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Recall P r e c i s i o n Fig. 6.5. Comparison of two retrieval algorithms based on their precision-recall curves Evaluation Using ...
Advances In Data Mining - Multimedia Applications and Theoretical ...
Petra Perner, 2009
4.1 Test Setup The general performance measures in information retrieval are Precision and Recall. Unlike most retrieval systems, the performance of our system depends heavily on the writer of the documents. Our system therefore has traits of ...
Advances In Computer Vision And Information Technology
K. V. Kale, 2008
Higher values of F1 indicate a more balanced combination between recall and precision. 4.3 Experimental Results In our experiment we have calculated recall, precision and F1, for different N values (recall that system generates top-N ...