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What is Pre-Processing

Encyclopedia of Information Science and Technology, Fourth Edition
A process of preparing a dataset in order to develop a mathematical model.
Published in Chapter:
Artificial Neural Networks and Their Applications in Business
Trevor J. Bihl (Air Force Institute of Technology, USA), William A. Young II (Ohio University, USA), and Gary R. Weckman (Ohio University, USA)
Copyright: © 2018 |Pages: 16
DOI: 10.4018/978-1-5225-2255-3.ch576
Abstract
Despite the natural advantage humans have for recognizing and interpreting patterns, large and complex datasets, as in Big Data, preclude efficient human analysis. Artificial neural networks (ANNs) provide a family of pattern recognition approaches for prediction, clustering and classification applicable to KDD with ANN model complexity ranging from simple (for small problems) highly complex (for large issues). To provide a starting point for readers, this chapter first describes foundational concepts that relate to ANNs. A listing of commonly used ANN methods, heuristics, and criteria for initializing ANNs is then discussed. Common pre- and post- data processing methods for dimensionality reduction and data quality issues are then described. The authors then provide a tutorial example of ANN analysis. Finally, the authors list and describe applications of ANNs to specific business related endeavors for further reading.
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Obtaining Deep Learning Models for Automatic Classification of Leukocytes
Includes processes like selection, cleaning, normalization, transformation feature extraction and transformation in order to obtain data that is more easily treatable.
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A Virtual Journey through 2D and 3D Elaborations Recorded with Range-Based and Image-Based Method: The Experience of Vitelleschi Palace in Tarquinia
The pre-processing phase is made of three main operations: recording, elaboration and decimation. The recording consists of the union of a couple or more point clouds; elaboration is made up by a set of operations: geo-referencing of the cloud on topo points (it consists in the roto-translation in space of each cloud in the global system), filtering (elimination of the points that have a high probability of not belonging to the object surface), selection (of the only points of the cloud covering the area of interest without any spatial resampling of these) and display of the scanworld as raw data; the decimation is the operation of reduction (resampling) of the spatial density of the points.
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Web Page Classification Using MDAWkNN
This helps in transforming raw data into a format suitable for the mining task. It is done apriori to the mining task and is more significant, as with no quality data, there is no quality mining results.
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A Novel Fuzzy Logic Classifier for Classification and Quality Measurement of Apple Fruit
It is the process by which the input images are filtered to remove noise, spike removal, etc. It is a very crucial step for further processing of input images.
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Do Web Site Visitors Vary in Their Search and Surf Behavior?
A step to create a meaningful data set from log files. Irrelevant entries, such as robot requests and graphic requests, and duplicated requests are generally removed from the data set.
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Thermal Analysis of Realistic Breast Model With Tumor and Validation by Infrared Images
Operations on images at the lowest level of abstraction in order to improve the image data.
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Artificial Neural Networks for Business Analytics
A process of preparing a dataset in order to develop a mathematical model.
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3D Image Acquisition and Analysis of Range Face Images for Registration and Recognition
It is the process by which the input raw images are filtered for noise, spike removal, etc. It is a very crucial step for further processing of input images.
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Artificial Neural Networks and Data Science
A process of preparing a dataset in order to develop a mathematical model.
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