Data Preparation for Data Mining- P4

... 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 8. Modeling the data 3.3.1 ... 3.4 Data preparation process transforms raw data into prepared training and test sets, together with the PIE-I and PIE-O modules. 3.1.2 Step 2: Survey the Data Mining includes surveying the data, ...

Data Preparation for Data Mining- P3

... 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, and for displaying ... the data set for mining—to best expose the information contained in it to the mining tool. Indeed, the whole purpose for mining data is to transform the information content of a data set that...

Data Preparation for Data Mining- P5

... 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 foundation for all preparation ... the data is the place to start. So what is the “hare” in data? The hare is the information content enfolded into the data set. Just as hare is the essence of the recipe for Jugged Hare, so information...

Data Preparation for Data Mining- P6

... 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. Fortunately, ... there is a data set CREDIT. This includes a sample of real-world credit information. One of the fields in that data set is “DAS,” which is a particular credit score rating. All of the data used...

Data Preparation for Data Mining- P7

... 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 example, either that ... from there to each of the nearest data points in each dimension. The mean distance to neighboring data points serves as a surrogate measurement for density. For many purposes this is a more...

Data Preparation for Data Mining- P8

... 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 exposing information, ... a working data preparation computer program were also addressed. In spite of the distance covered here, there remains much to do to the data before it is fully prepared for surveying...

Data Preparation for Data Mining- P9

... 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 encountered. ... are present. To find the necessary context for replacement, therefore, it is necessary to look at the data set as a whole. 8.1 Retaining Information about Missing Values Missing...

Tài liệu Data Preparation for Data Mining- P10 docx

... 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 information is best ... Figure 9.11 Waterforms and their correlograms. 9.4 Modeling Series Data Given these tools for describing series data, how do they help with preparing the data for modeling? There...

Tài liệu Data Preparation for Data Mining- P11 pdf

... 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. The formula for ... 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. The formula for...

Tài liệu Data Preparation for Data Mining- P12 pptx

... 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 different points of view. ... prepared data set to glean information that is useful to the miner. Preparation manipulates values; surveying answers questions. In general, a miner has limited data. When the data is...

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