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Illustrated three stages of data mining process?
Stage 1: Exploration: This stage generally starts along with data preparation that may involve cleaning data, selecting subsets of records, data transformations and in case of data sets along with large numbers of variables as "fields" performing several preliminary feature selection operations to bring the number of variables to a manageable range (i.e., depending upon the statistical methods that are being important).
Stage 2: Model building and validation: on this stage involves considering different models and choosing the best one based upon their predictive performance (which are explaining the variability into question and producing stable results across some samples). There are a variety of methods developed to achieve that goal, which many of are based on so-called the "competitive evaluation of models," which is, applying various models to similar data set and after that comparing their performance to decide the best.
Stage 3: Deployment: That last stage involves using the model selected like best in the earlier stage and applying this to new data in order to produce predictions or estimates of the expected outcome.
Suppose that a process scheduling algorithm favors those processes that have used the least processor time in the recent past. Why will this algorithm favour I/O- bound processes,
HCP
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