A Novel Data Hiding Method for Two-Color Images by Pan, Wu

By Pan, Wu

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However, such noises can be useful in some cases, where unusual items or exceptions are major concerns. Examples are fraud detection, unusual usage patterns and remarkable response patterns. - 35 - The challenge is to distinguish the outliers from the errors. When performing data understanding phase, data cleaning and scrubbing is required. This step includes finding erroneous data and trying to fix them. Thus, the possibility to detect interesting differentiation might be diminished. On the other hand, if the incorrect data remained in the data sets, the accuracy of the model would be compromised.

Generic tasks of this phase include data organization, data collection, data description, data analysis, data exploration and data quality verification. At the end of the phase, the results of all above-mentioned tasks have to be reported. 3. Data Preparation As mentioned above, one of the major concerns in using data mining technique is the quality of data. The objective of this phase is to ensure that data sets are ready to be mined. The process includes data selection (deciding on which data is relevant), data cleaning (removing all, or most, incompleteness, noises and inconsistency), data scrubbing (cleaning data by abrasive action), data integration (combining data from multiple sources into standardized format), data transformation (converting standardized data into ready-to-be-mined and standardized format) and data reduction (removing redundancies and merging data into aggregated format).

The objective of this analysis is to separate data with similar characteristics from the dissimilar ones. The difference between clustering and classification is that while clustering does not require pre-identified class labels, classification does. That is why classification is also called supervised learning while clustering is called unsupervised learning. As mentioned above, sometimes it is more convenient to analyze data in the aggregated form and allow breaking down into details if needed.

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