ibeacon precision

tree.Expiry of HrtimerHrtimer in the Hrtimer_run_queues function to determine whether the execution is due. The Hrtimer_run_queues call chain is: Linux's system clock function->update_process_times->run_local_timers->hrtimer_run_queues.void Hrtimer_run_queues (void)Determines whether the high-precision mode, if it is high-precision mode, returns immediately. This article does not consider this situation te

I have been looking for precision and recall how to calculate, because always call the function of the relationship, I thought that TensorFlow has been encapsulated to write such a call method, has not been found, seems to be too lazy, lost the desire to do, in the following address to see the code written by others, Although it can not be used, it is also very important to inspire. Https://gist.github.com/Mistobaan/337222ac3acbfc00bdac def tf_confu

Original article: http://demon.tw/copy-paste/javascript-precision.html Precision loss of small numbers and big integers in Javascript Title: Precision loss of small numbers and big integers in JavascriptAuthor: demonLink: http://demon.tw/copy-paste/javascript-precision.htmlCopyright: all articles in this blog comply with the terms of the "signature-non-commercial use-share 2.5 mainland China" agreement.

Because of the retrieval, I need to use the accuracy and recall rate (Precision-recall) index to measure the validity of the retrieval algorithm. As we all know, the precision-recall curve usually shows a downward trend, and even if the same retrieval method is used to retrieve different retrieval cases, the higher the accuracy rate of the search results, the lower the recall rate will always be. I am curio

Reason: JS in accordance with the 2 to deal with decimal subtraction, on the basis of arg1 arg2 precision extension or reverse expansion matching, so will appear as follows. JavaScript (JS) decimal point subtraction problem, is a JS bug such as 0.3*1 = 0.2999999999, the following list can be perfect to find the corresponding accuracy of the four JS algorithm function Accdiv (arg1,arg2) {var t1=0,t2=0,r1,r2; Try{t1=arg1.tostring (). Split (".") [

BC is the abbreviation for binary calculator. The parameters of the bc* function are the operands plus an optional [int scale], such as String Bcadd (String $left _operand, String $right _operand[, int $scale]), assuming scale does not provide , the default value of Bcscale is used. Here the large number is directly represented by a string of 0-9, and the result of the calculation is also a string.Bcadd-adds two high-precision numbersbccomp-two high-

I want to learn about the precision of javascript floating-point numbers, so that you can understand the real precision of JavaScript floating-point numbers, you can refer to the several numeric data types in most programming languages, but JavaScript has only one type. You can use the typeof operator to view the numeric type. JavaScript classifies integers and floating-point numbers as numbers. typeof 1

1. Accuracy rate and Recall rate (Precision Recall) Accuracy and recall rates are two measures widely used in the field of information retrieval and statistical classification to evaluate the quality of the results. The accuracy is to retrieve the number of related documents and the total number of documents retrieved, to measure the precision of the retrieval system; Recall is the ratio of the number of d

automatically omits the highest 1, so the storage is 23 bits actually 24 bits. (Decimal position is 2^ (23) =8388608 7 digits calculated as 6-digit precision)For a chestnut: 3.2fConvert to binary storage: integral part 32 binary 11Fractional part 0.2 is converted to binary (by 2 to the integer portion until the fractional part is divided into 0)----> (decimal by 2) 0.4 0.8 1.6 1.2 0.4 0.8 1.6 1.2 0.4 ... (Infinite Loop)The result is: 11.00 1100 11001

This article mainly introduces the PHP floating point Precision problem summary, this article discusses the PHP floating point precision loss problem emphatically, uses the three paragraph different way to explain this question formation reason and the solution, needs the friend to be possible to refer to under A, PHP floating point accuracy loss problem Let's look at the following code: The code is as f

Meaning Give n high precision numbers to determine whether the equal ratio sequence. Range: 0 Analysis: According to the question, this problem must be solved with high precision, using the array simulation multiplication calculation process. Determine whether the equal-ratio sequence method: a[i],a[i+1],a[i+2], for arbitrary I, have a[i]*a[i+2]=a[i+1]*a[i+1]. Therefore, a high-

Recently used in the temperature and humidity sensor, AM2305 drive, single bus, on the power of at least 2S to read temperature and humidity, temperature accuracy is high, like DS18B20, data with the checksum, will not appear ds18b20, and the timing is not high /************************************************************************************************************* * FileName: am2305.c * function: STM32 AM2305 high precision temperature and hu

Pdop: Position dilution of precision. It is translated as "precision intensity" and is usually translated as "relative error ". The specific meaning is: because the quality of the observed results is related to the geometric shape between the measured man-made satellite and the receiver, therefore, calculating the error volume caused by the above is called the strength of accuracy. The better the satellite

BC is the abbreviation for binary calculator. The arguments to the bc* function are the operands plus an optional [int scale], such as String Bcadd (String $left _operand, String $right _operand[, int $scale]), if scale is not provided , the default value of Bcscale is used. Here the large number is directly represented by a string of 0-9, and the result of the calculation is also a string.Bcadd-adds two high-precision numbersBccomp-compares two high-

yu Code Comments Machine learning (ML), Natural language Processing (NLP), Information Retrieval (IR) and other fields, evaluation (Evaluation) is a necessary work, and its evaluation indicators tend to have the following points: accuracy (accuracy), accuracy (Precision), Recall (Recall) and F1-measure. (Note: In contrast, the IR ground truth is often a Ordered List, not a Bool type of Unordered Collection, in the case of all found, ranked third or f

Trade-offs between Preision and recallIs still an example of cancer prediction, when predicted as cancer, y=1; generally as a logistic regression we are hθ when >=0.5 (x) Y=1;When we want to be more confident in predicting cancer (for patients who say they have cancer that will have a significant effect on them, let them go to therapy, so be more sure to tell the patient cancer predictions): We can set the threshold to 0.7, At this point we will have a high