It takes the average reader 3 hours to read Advances in K-means Clustering by Junjie Wu
Assuming a reading speed of 250 words per minute. Learn more
Nearly everyone knows K-means algorithm in the fields of data mining and business intelligence. But the ever-emerging data with extremely complicated characteristics bring new challenges to this "old" algorithm. This book addresses these challenges and makes novel contributions in establishing theoretical frameworks for K-means distances and K-means based consensus clustering, identifying the "dangerous" uniform effect and zero-value dilemma of K-means, adapting right measures for cluster validity, and integrating K-means with SVMs for rare class analysis. This book not only enriches the clustering and optimization theories, but also provides good guidance for the practical use of K-means, especially for important tasks such as network intrusion detection and credit fraud prediction. The thesis on which this book is based has won the "2010 National Excellent Doctoral Dissertation Award", the highest honor for not more than 100 PhD theses per year in China.
Advances in K-means Clustering by Junjie Wu is 180 pages long, and a total of 45,000 words.
This makes it 61% the length of the average book. It also has 55% more words than the average book.
The average oral reading speed is 183 words per minute. This means it takes 4 hours and 5 minutes to read Advances in K-means Clustering aloud.
Advances in K-means Clustering is suitable for students ages 10 and up.
Note that there may be other factors that effect this rating besides length that are not factored in on this page. This may include things like complex language or sensitive topics not suitable for students of certain ages.
When deciding what to show young students always use your best judgement and consult a professional.
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