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be challenged and removed. (March 2013) (Learn how and when to remove this template message) In digital transmission, the number of bit errors is the number of received bits of a data stream over a communication channel that have been altered due to noise, error rate formula interference, distortion or bit synchronization errors. The bit error rate (BER) is the number of how to calculate bayes error rate bit errors per unit time. The bit error ratio (also BER) is the number of bit errors divided by the total number of error rate calculation transferred bits during a studied time interval. BER is a unitless performance measure, often expressed as a percentage.[1] The bit error probability pe is the expectation value of the bit error ratio. The bit error ratio can be https://en.wikipedia.org/wiki/Error_rate considered as an approximate estimate of the bit error probability. This estimate is accurate for a long time interval and a high number of bit errors. Contents 1 Example 2 Packet error ratio 3 Factors affecting the BER 4 Analysis of the BER 5 Mathematical draft 6 Bit error rate test 6.1 Common types of BERT stress patterns 7 Bit error rate tester 8 See also 9 References 10 External links Example[edit] As an example, assume https://en.wikipedia.org/wiki/Bit_error_rate this transmitted bit sequence: 0 1 1 0 0 0 1 0 1 1 and the following received bit sequence: 0 0 1 0 1 0 1 0 0 1, The number of bit errors (the underlined bits) is, in this case, 3. The BER is 3 incorrect bits divided by 10 transferred bits, resulting in a BER of 0.3 or 30%. Packet error ratio[edit] The packet error ratio (PER) is the number of incorrectly received data packets divided by the total number of received packets. A packet is declared incorrect if at least one bit is erroneous. The expectation value of the PER is denoted packet error probability pp, which for a data packet length of N bits can be expressed as p p = 1 − ( 1 − p e ) N {\displaystyle p_{p}=1-(1-p_{e})^{N}} , assuming that the bit errors are independent of each other. For small bit error probabilities, this is approximately p p ≈ p e N . {\displaystyle p_{p}\approx p_{e}N.} Similar measurements can be carried out for the transmission of frames, blocks, or symbols. Factors affecting the BER[edit] In a communication system, the receiver side BER may be affected by transmission channel noise, interference, distortion, bit synchronization problems, attenuation, wireless multipath fading, etc. The BER may be improved by choosing a strong signal strength (unless this causes cross-talk and more
here for a quick overview of the site Help Center Detailed answers to any questions you might have Meta Discuss the workings and policies of this site About Us Learn more about Stack Overflow the company Business Learn more about hiring developers or posting ads with us Stack http://stackoverflow.com/questions/10067118/how-to-calculate-classification-error-rate Overflow Questions Jobs Documentation Tags Users Badges Ask Question x Dismiss Join the Stack Overflow Community Stack Overflow is a community of 4.7 million programmers, just like you, helping each other. Join them; it only takes a minute: Sign up How to calculate classification error rate up vote 1 down vote favorite Alright. Now this question is pretty hard. I am going to give you an example. Now the left numbers are my algorithm classification and the right numbers are the original class numbers 177 86 177 error rate 86 177 86 177 86 177 86 177 86 177 86 177 86 177 86 177 89 177 89 177 89 177 89 177 89 177 89 177 89 So here my algorithm merged 2 different classes into 1. As you can see it merged class 86 and 89 into one class. So what would be the error at the above example ? Or here another example 203 7 203 7 203 7 203 7 16 7 203 7 17 7 16 7 203 7 At error rate wiki the above example left numbers are my algorithm classification and the right numbers are original class ids. As can be seen above it miss classified 3 products (i am classifying same commercial products). So at this example what would be the error rate? How would you calculate. This question is pretty hard and complex. We have finished the classification but we are not able to find correct algorithm for calculating success rate :D algorithm cluster-analysis classification ratio confusion-matrix share|improve this question edited May 11 '13 at 16:26 denis 10.5k43855 asked Apr 8 '12 at 22:36 MonsterMMORPG 6,14741121220 add a comment| 4 Answers 4 active oldest votes up vote 2 down vote accepted Here's a longish example, a real confuson matrix with 10 input classes "0" - "9" (handwritten digits), and 10 output clusters labelled A - J. Confusion matrix for 5620 optdigits: True 0 - 9 down, clusters A - J across ----------------------------------------------------- A B C D E F G H I J ----------------------------------------------------- 0: 2 4 1 546 1 1: 71 249 11 1 6 228 5 2: 13 5 64 1 13 1 460 3: 29 2 507 20 5 9 4: 33 483 4 38 5 3 2 5: 1 1 2 58 3 480 13 6: 2 1 2 294 1 1 257 7: 1 5 1 546 6 7 8: 415 15 2 5 3 12 13 87 2 9: 46 72 2 357 35 1 47 2 ---------------------------------------------------- 580 383 496 1002 307 670 549 557 810 266 estimates in each clust
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