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The implementation of exception handling in programming languages typically involves a fair amount of support from both a code generator and the runtime system accompanying a compiler. (It was the addition of exception handling to C++ that ended the useful lifetime of the original C++ compiler, Cfront. [18]) Two schemes are most common.
Common exceptions include an invalid argument (e.g. value is outside of the domain of a function), [5] an unavailable resource (like a missing file, [6] a network drive error, [7] or out-of-memory errors [8]), or that the routine has detected a normal condition that requires special handling, e.g., attention, end of file. [9]
The difference between data analysis and data mining is that data analysis is used to test models and hypotheses on the dataset, e.g., analyzing the effectiveness of a marketing campaign, regardless of the amount of data. In contrast, data mining uses machine learning and statistical models to uncover clandestine or hidden patterns in a large ...
Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]
The output of a cryptographic hash function, also known as a message digest, can provide strong assurances about data integrity, whether changes of the data are accidental (e.g., due to transmission errors) or maliciously introduced. Any modification to the data will likely be detected through a mismatching hash value.
A variety of data re-sampling techniques are implemented in the imbalanced-learn package [1] compatible with the scikit-learn Python library. The re-sampling techniques are implemented in four different categories: undersampling the majority class, oversampling the minority class, combining over and under sampling, and ensembling sampling.
Code written in VBA is compiled [6] to Microsoft P-Code (pseudo-code), a proprietary intermediate language, which the host applications (Access, Excel, Word, Outlook, and PowerPoint) store as a separate stream in COM Structured Storage files (e.g., .doc or .xls) independent of the document streams.
One set, the bootstrap sample, is the data chosen to be "in-the-bag" by sampling with replacement. The out-of-bag set is all data not chosen in the sampling process. When this process is repeated, such as when building a random forest, many bootstrap samples and OOB sets are created. The OOB sets can be aggregated into one dataset, but each ...