... Transformations and Difficulties—Variables, Data, and Information Much of this discussion has pivoted on information—information in a data set, information content of various scales, and transforming ... their limited data capacity and inability to handle certain types of operations needed in data preparation, data surveying, and data modeling. For exploring small data sets, a...
... execution data is in its “raw” form, and the model works only with prepared data, it is necessary to transform the execution data in the same way that the training and test data were transformed. ... Accessing the data 2. Auditing the data 3. Enhancing and enriching the data 4. Looking for sampling bias 5. Determining data structure 6. Building the PIE 7. Surveying the data...
... original data set. The data preparation software creates
this variable and captures information about the missing value patterns. For each pattern
of missing values in the data set, the data preparation ... where the
data comes from, what is in the data, and what issues remain to be established—in other
words, to determine the general quality of the data. This forms the f...
... the original data sample. Random
sampling does that. If the original data set represents a biased sample, that is evaluated
partly in the data assay (Chapter 4), again when the data set itself ... what a data miner starts with as a source data set is almost
always a sample and not the population. When preparing variables, we cannot be sure
that the original data is bias free...
... include such
features as creating a pseudo-variable for “North,” one for “South,” another for “East,” one
for “West,” and perhaps others for other features of interest, such as population density ... of pseudo-variable inputs for each alpha
label—that is, for this example, a unique pattern for each item in the produce department.
The domain expert must make sure, for exam...
... Translating the information discovered there into insights
about the data, and the objects the data represents, forms an important part of the data
survey in addition to its use in data preparation. ... putting data into the multitable structures called “normal form” in a
database, data warehouse, or other data repository.) During the process of manipulation, as
well as expo...
...
Third, and very important for maximum information exposure, the individual variable
distributions are transformed. This transformation makes the between-variable
information far more accessible ... least harm to the information content of the data set. Yet it still
leaves some information exposed for the mining tools to use when values outside those
within the sample data set are...
... Series Data
Series data differs from the forms of data so far discussed mainly in the way in which the
data enfolds the information. The main difference is that the ordering of the data ... Preparing series data for modeling, then,
must preserve the nature of the pattern that exists. Preparation also includes putting the
data into a form in which the desired inform...
... extracting information from noisy or distorted series data. They have
involved extracting a variety of waveforms from the original waveform that emphasize
particular aspects of the data useful for modeling. ... transform accomplishes this. The second transform subtracts the mean of the
transformed variable from each transformed value, and divides the result by the standard
deviation....
... of the survey, rather than data
preparation? Data preparation concentrates on transforming and adjusting variables’
values to ensure maximum information exposure. Data surveying concentrates ... density manifold stability.
But here is where data preparation steps into the data survey. The data survey
(Chapter 11) examines the data set as a whole from many differe...