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Standard Error Classification Accuracy

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Difference Between Accuracy And Precision

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Sklearn Accuracy Naive Bayes

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Accuracy Formula

policies of this site About Us Learn more about Stack Overflow the accuracy and precision examples company Business Learn more about hiring developers or posting ads with us Cross Validated Questions Tags Users Badges Unanswered accuracy and precision in chemistry Ask Question _ Cross Validated is a question and answer site for people interested in statistics, machine learning, data analysis, data mining, and data visualization. Join them; it only takes a http://www.ncbi.nlm.nih.gov/pubmed/25228494 minute: Sign up Here's how it works: Anybody can ask a question Anybody can answer The best answers are voted up and rise to the top Estimating classifier performance using cross validation, average accuracy and standard deviation and up vote 0 down vote favorite 1 I want to estimate a classifier accuracy on benchmark data. Data is not split into training and http://stats.stackexchange.com/questions/211805/estimating-classifier-performance-using-cross-validation-average-accuracy-and-s testing so I use 5-fold cross validation, using 80% of data as training and testing on 20%. Each test is repeated 20 times, so in total there are 100 runs (20 test runs * 5 tests on each fold) Accuracy is defined as number of correct predictions divided by number of records in a training data I do not know how to calculate average accuracy and its standard deviation: Should results from each fold be averaged and then the stdev calculated on 20 samples? or Should I calculate average and stdev on all 100 samples? Another question is should STDEV or STDEVP function be used to calculate standard deviation, they are defined as follows: STDEVP - Calculates standard deviation based on the entire population given as arguments. STDEV - Estimates standard deviation based on a sample. classification cross-validation standard-deviation average accuracy share|improve this question asked May 10 at 11:33 Sebastian Widz 714 add a comment| 2 Answers 2 active oldest votes up vote 2 down vote How to calculate standard deviation depends on which standard deviation you need. Your results are subject to (

CAMPUSLOGIN Classification Accuracy Assessment PrintIn the context of information extraction by image analysis, accuracy “measures the agreement between a standard assumed to be correct and a classified image of unknown quality.” (Campbell, 2007) Precision defines the level https://www.e-education.psu.edu/geog883/node/524 of detail found within the classification. It is possible to increase the accuracy of a classification by decreasing the amount of detail or by generalizing to broad classes rather than very specific ones. For example, a scheme which generally categorizes trees vs. crops presents less opportunity for classification error than one that distinguishes many types of trees and many types accuracy and of crops. In this case, lower precision provides the potential for higher accuracy. However, the user of the map that offers only general classes cannot make precise statements about any given point on the map. Classification error occurs when a pixel (or feature) belonging to one category is assigned to another category. Errors of omission occur when a feature accuracy and precision is left out of the category being evaluated; errors of commission occur when a feature is incorrectly included in the category being evaluated. An error of omission in one category will be counted as an error in commission in another category. Accuracy assessment is performed by comparing the map created by remote sensing analysis to a reference map based on a different information source. One might ask why the remote sensing analysis is needed if the reference map to compare it to already exists. One of the primary purposes of accuracy assessment and error analysis in this case is to permit quantitative comparisons of different interpretations. Classifications done from images acquired at different times, classified by different procedures, or produced by different individuals can be evaluated using a pixel-by-pixel, point-by-point comparison. The results must be considered in the context of the application to determine which is the “most correct” or “most useful” for a particular purpose. In order to be compared, both the map to be evaluated and the reference map must be accurately registered geometrically to

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