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The boot code in the VBR can assume that the BIOS has set up its data structures and interrupts and initialized the hardware. The code should not assume more than 32 KB of memory to be present for fail-safe operation; [1] if it needs more memory it should query INT 12h for it, since other pre-boot code (such as f.e. BIOS extension overlays, encryption systems, or remote bootstrap loaders) may ...
Variable bitrate (VBR) is a term used in telecommunications and computing that relates to the bitrate used in sound or video encoding. As opposed to constant bitrate (CBR), VBR files vary the amount of output data per time segment.
An example of data mining related to an integrated-circuit (IC) production line is described in the paper "Mining IC Test Data to Optimize VLSI Testing." [12] In this paper, the application of data mining and decision analysis to the problem of die-level functional testing is described. Experiments mentioned demonstrate the ability to apply a ...
In computing, the BIOS parameter block, often shortened to BPB, is a data structure in the volume boot record (VBR) describing the physical layout of a data storage volume. On partitioned devices, such as hard disks , the BPB describes the volume partition, whereas, on unpartitioned devices, such as floppy disks , it describes the entire medium.
There have been some efforts to define standards for the data mining process, for example, the 1999 European Cross Industry Standard Process for Data Mining (CRISP-DM 1.0) and the 2004 Java Data Mining standard (JDM 1.0). Development on successors to these processes (CRISP-DM 2.0 and JDM 2.0) was active in 2006 but has stalled since.
Semantic data mining is a subset of data mining that specifically seeks to incorporate domain knowledge, such as formal semantics, into the data mining process.Domain knowledge is the knowledge of the environment the data was processed in. Domain knowledge can have a positive influence on many aspects of data mining, such as filtering out redundant or inconsistent data during the preprocessing ...
Perhaps the simplest example is storing values of bytes as differences (deltas) between sequential values, rather than the values themselves. So, instead of 2, 4, 6, 9, 7, we would store 2, 2, 2, 3, −2. This reduces the variance (range) of the values when neighbor samples are correlated, enabling a lower bit usage for the same data.
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]