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  2. AMD Am2900 - Wikipedia

    en.wikipedia.org/wiki/AMD_Am2900

    AMD Am2901: 4-bit-slice ALU. Am2900 is a family of integrated circuits (ICs) created in 1975 by Advanced Micro Devices (AMD). They were constructed with bipolar devices, in a bit-slice topology, and were designed to be used as modular components each representing a different aspect of a computer control unit (CCU).

  3. Standard error - Wikipedia

    en.wikipedia.org/wiki/Standard_error

    Download as PDF; Printable version; In other projects ... and we could use this value to calculate ... the mean and standard deviation are descriptive statistics ...

  4. AMD Am29000 - Wikipedia

    en.wikipedia.org/wiki/AMD_Am29000

    The AMD Am29000, commonly shortened to 29k, is a family of 32-bit RISC microprocessors and microcontrollers developed and fabricated by Advanced Micro Devices (AMD). Based on the seminal Berkeley RISC , the 29k added a number of significant improvements.

  5. Process capability index - Wikipedia

    en.wikipedia.org/wiki/Process_capability_index

    If the upper and lower specification limits of the process are USL and LSL, the target process mean is T, the estimated mean of the process is ^ and the estimated variability of the process (expressed as a standard deviation) is ^, then commonly accepted process capability indices include:

  6. Symmetric mean absolute percentage error - Wikipedia

    en.wikipedia.org/wiki/Symmetric_mean_absolute...

    In contrast to the mean absolute percentage error, SMAPE has both a lower and an upper bound. Indeed, the formula above provides a result between 0% and 200%. Indeed, the formula above provides a result between 0% and 200%.

  7. AMD Shares Are Very Expensive, but Should You Ignore the ...

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  8. Loss function - Wikipedia

    en.wikipedia.org/wiki/Loss_function

    In many applications, objective functions, including loss functions as a particular case, are determined by the problem formulation. In other situations, the decision maker’s preference must be elicited and represented by a scalar-valued function (called also utility function) in a form suitable for optimization — the problem that Ragnar Frisch has highlighted in his Nobel Prize lecture. [4]

  9. Average variance extracted - Wikipedia

    en.wikipedia.org/wiki/Average_variance_extracted

    The average variance extracted has often been used to assess discriminant validity based on the following "rule of thumb": the positive square root of the AVE for each of the latent variables should be higher than the highest correlation with any other latent variable.