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  2. Numeric precision in Microsoft Excel - Wikipedia

    en.wikipedia.org/wiki/Numeric_precision_in...

    With some exceptions regarding erroneous values, infinities, and denormalized numbers, Excel calculates in double-precision floating-point format from the IEEE 754 specification [1] (besides numbers, Excel uses a few other data types [2] ). Although Excel allows display of up to 30 decimal places, its precision for any specific number is no ...

  3. Positive and negative predictive values - Wikipedia

    en.wikipedia.org/wiki/Positive_and_negative...

    The positive predictive value (PPV), or precision, is defined as = + = where a "true positive" is the event that the test makes a positive prediction, and the subject has a positive result under the gold standard, and a "false positive" is the event that the test makes a positive prediction, and the subject has a negative result under the gold standard.

  4. Circular error probable - Wikipedia

    en.wikipedia.org/wiki/Circular_error_probable

    Main page; Contents; Current events; Random article; About Wikipedia; Contact us; Donate; Pages for logged out editors learn more

  5. Unit in the last place - Wikipedia

    en.wikipedia.org/wiki/Unit_in_the_last_place

    Unit in the last place. In computer science and numerical analysis, unit in the last place or unit of least precision ( ulp) is the spacing between two consecutive floating-point numbers, i.e., the value the least significant digit (rightmost digit) represents if it is 1. It is used as a measure of accuracy in numeric calculations.

  6. Single-precision floating-point format - Wikipedia

    en.wikipedia.org/wiki/Single-precision_floating...

    Single-precision floating-point format (sometimes called FP32 or float32) is a computer number format, usually occupying 32 bits in computer memory; it represents a wide dynamic range of numeric values by using a floating radix point . A floating-point variable can represent a wider range of numbers than a fixed-point variable of the same bit ...

  7. Precision and recall - Wikipedia

    en.wikipedia.org/wiki/Precision_and_recall

    To calculate the recall for a given class, we divide the number of true positives by the prevalence of this class (number of times that the class occurs in the data sample). The class-wise precision and recall values can then be combined into an overall multi-class evaluation score, e.g., using the macro F1 metric .

  8. Confusion matrix - Wikipedia

    en.wikipedia.org/wiki/Confusion_matrix

    In predictive analytics, a table of confusion (sometimes also called a confusion matrix) is a table with two rows and two columns that reports the number of true positives, false negatives, false positives, and true negatives. This allows more detailed analysis than simply observing the proportion of correct classifications (accuracy).

  9. Arbitrary-precision arithmetic - Wikipedia

    en.wikipedia.org/wiki/Arbitrary-precision_arithmetic

    Arbitrary precision. v. t. e. In computer science, arbitrary-precision arithmetic, also called bignum arithmetic, multiple-precision arithmetic, or sometimes infinite-precision arithmetic, indicates that calculations are performed on numbers whose digits of precision are potentially limited only by the available memory of the host system.

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