Books > Computing & IT > General theory of computing
|
Buy Now
Mining Imperfect Data - With Examples in R and Python (Paperback, 2nd Revised edition)
Loot Price: R2,778
Discovery Miles 27 780
|
|
Mining Imperfect Data - With Examples in R and Python (Paperback, 2nd Revised edition)
Series: Mathematics in Industry
Expected to ship within 12 - 17 working days
|
It has been estimated that as much as 80% of the total effort in a
typical data analysis project is taken up with data preparation,
including reconciling and merging data from different sources,
identifying and interpreting various data anomalies, and selecting
and implementing appropriate treatment strategies for the anomalies
that are found. This book focuses on the identification and
treatment of data anomalies, including examples that highlight
different types of anomalies, their potential consequences if left
undetected and untreated, and options for dealing with them. As
both data sources and free, open-source data analysis software
environments proliferate, more people and organizations are
motivated to extract useful insights and information from data of
many different kinds (e.g., numerical, categorical, and text). The
book emphasizes the range of open-source tools available for
identifying and treating data anomalies, mostly in R but also with
several examples in Python. Mining Imperfect Data: With Examples in
R and Python, Second Edition presents a unified coverage of 10
different types of data anomalies (outliers, missing data, inliers,
metadata errors, misalignment errors, thin levels in categorical
variables, noninformative variables, duplicated records, coarsening
of numerical data, and target leakage); includes an in-depth
treatment of time-series outliers and simple nonlinear digital
filtering strategies for dealing with them; and provides a detailed
introduction to several useful mathematical characteristics of
important data characterizations that do not appear to be widely
known among practitioners, such as functional equations and key
inequalities.
General
Imprint: |
Society For Industrial & Applied Mathematics,U.S.
|
Country of origin: |
United States |
Series: |
Mathematics in Industry |
Release date: |
August 2020 |
Authors: |
Ronald K. Pearson
|
Format: |
Paperback
|
Pages: |
481 |
Edition: |
2nd Revised edition |
ISBN-13: |
978-1-61197-626-7 |
Categories: |
Books >
Computing & IT >
General theory of computing >
General
|
LSN: |
1-61197-626-X |
Barcode: |
9781611976267 |
Is the information for this product incomplete, wrong or inappropriate?
Let us know about it.
Does this product have an incorrect or missing image?
Send us a new image.
Is this product missing categories?
Add more categories.
Review This Product
No reviews yet - be the first to create one!
|
|
Email address subscribed successfully.
A activation email has been sent to you.
Please click the link in that email to activate your subscription.