Principal manifolds for data visualization and dimension reduction
A. N. Gorbanʹ
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at 250 WPM5h 34m
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Principal manifolds for data visualization and dimension reduction
Published
2007
Publisher
Springer
Pages
334
ISBN-13
9783540737490
ISBN-10
3540737499
Subjects
Principal component analysis
Principal component analysis
Constrained Principal Component Analysis and Related Techniques
Principal components analysis
Independent component analysis
Independent component analysis
Frequently Asked Questions
How many pages are in Principal manifolds for data visualization and dimension reduction?
This edition of Principal manifolds for data visualization and dimension reduction has approximately 334 pages. Please note, this is an estimate and the exact page count can vary between hardcover, paperback, and e-book versions.
How long does it take to read Principal manifolds for data visualization and dimension reduction?
For most readers, Principal manifolds for data visualization and dimension reduction typically takes between 6h 58m and 4h 38m to complete. This is based on the book's length of approximately 83,500 words and common reading speeds.
Here's a detailed breakdown: • Continuous reading at 250 WPM: approximately 5h 34m of focused reading • Casual reading (30 minutes/day): you could finish in roughly 12 days • Estimated word count: 83,500 words
Your individual reading time will vary based on your personal reading pace, the amount of daily reading time, and your familiarity with the subject matter.
What is the word count of Principal manifolds for data visualization and dimension reduction?
The estimated word count for Principal manifolds for data visualization and dimension reduction is approximately 83,500 words. This figure is calculated using industry-standard methods that consider genre-specific word density patterns, typical formatting and layout characteristics, and standard words-per-page ratios for published books.
This is an approximation — actual word count may vary based on font size, formatting, edition, and the presence of illustrations or charts.
Who is the author of Principal manifolds for data visualization and dimension reduction?
Principal manifolds for data visualization and dimension reduction was written by A. N. Gorbanʹ.
When was Principal manifolds for data visualization and dimension reduction published?
The publication date for this specific edition is 2007. The original work may have been published on a different date.