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Could you derive something useful from the data?
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The final representation of data constructed by the deep learning algorithm (output of the final layer) provides useful information from the data which can be used as features in building classifiers, or even can be used for data indexing and other applications which are more efficient when using abstract representations of data rather than high dimensional sensory data.
Scalability Operating efficiently large amount of medical data (especially image data) and extracting potentially useful information from the data in order to reduce medical errors are crucial jobs.
Metered energy use data contain anomalies and bias, and those must be flagged and investigated to reach useful conclusions from the data.
The new algorithms can extract useful features from the data corrupted by impulsive noises (or outliers) in a more effective way.
Although there exist commercial products for data analysis [83 86], most of the studies on the traditional data analysis are focused on the design and development of efficient and/or effective "ways" to find the useful things from the data.
The data scientists nowadays can pay more attention to finding out the useful information from the data even thought this task is typically like looking for a needle in a haystack.
In fact, the problems of analyzing the large scale data were not suddenly occurred but have been there for several years because the creation of data is usually much easier than finding useful things from the data.
Assuming that we have obtained a certain amount of radar returns from different walls, before the training phase, a procedure called feature extraction, which extracts the useful information from the data or transforms the data into an appropriate format, should be done to produce the feature vectors.
Of the 288 assays attempted on the Sequenom MassArray platform, 241 (83.7%) assays yielded a sufficient number of genotypes to draw useful conclusions from the data (>70% call rate) across all 128 DNA samples.
Experiments may also be designed optimally to maximize the probability to achieve useful information from the data, as we will mention below.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com