Are you looking for the best Introduction To Data Mining Techniques? Based on expert reviews, we ranked them. We've listed our top-ranked picks, including the top-selling Introduction To Data Mining Techniques.
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- Igual, Laura (Author)
- English (Publication Language)
- 232 Pages - 03/02/2017 (Publication Date) - Springer (Publisher)
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- 334 Pages - 08/05/2019 (Publication Date) - Chapman and Hall/CRC (Publisher)
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- English (Publication Language)
- 424 Pages - 03/31/2020 (Publication Date) - Cambridge University Press (Publisher)
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- Pinheiro, Dr. Carlos Andre Reis Andre Reis (Author)
- English (Publication Language)
- 170 Pages - 08/06/2021 (Publication Date) - SAS Institute (Publisher)
- Bernard, Etienne (Author)
- English (Publication Language)
- 424 Pages - 12/20/2021 (Publication Date) - Wolfram Media (Publisher)
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- English (Publication Language)
- 856 Pages - 10/15/2019 (Publication Date) - O'Reilly Media (Publisher)
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- English (Publication Language)
- 891 Pages - 03/23/2011 (Publication Date) - Wiley (Publisher)
- Amazon Kindle Edition
- Stamile, Claudio (Author)
- English (Publication Language)
- 338 Pages - 06/25/2021 (Publication Date) - Packt Publishing (Publisher)
- Wire-o bound with high visibility yellow cover
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- Hardcover Book
- Cheng, Chi-Hao (Author)
- English (Publication Language)
- 177 Pages - 09/16/2021 (Publication Date) - River Publishers (Publisher)
- Jamsa, Kris (Author)
- English (Publication Language)
- 668 Pages - 02/17/2020 (Publication Date) - Jones & Bartlett Learning (Publisher)
- This book presents some of the most important modeling and prediction techniques, along with relevant applications
- Topics include linear regression, classification, re-sampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering,...
- Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other...
- Hardcover Book
- James, Gareth (Author)
- Amazon Kindle Edition
- Theobald, O (Author)
- English (Publication Language)
- 164 Pages - 06/21/2017 (Publication Date) - Scatterplot Press (Publisher)
- Hardcover Book
- Taddy, Matt (Author)
- English (Publication Language)
- 352 Pages - 08/21/2019 (Publication Date) - McGraw Hill (Publisher)
- Mit Press
- Guttag, John V. (Author)
- English (Publication Language)
- 466 Pages - 08/12/2016 (Publication Date) - The MIT Press (Publisher)
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FAQ:
Q: What are basic data mining techniques?
A: Data Mining definition: Data Mining is all about explaining the past and predicting the future via Data analysis. Data mining helps to extract information from huge sets of data. … Data mining process includes business understanding,Data Understanding,Data Preparation,Modelling,Evolution,Deployment.
Q: What are outliers in data mining?
A: In data mining, outliers are data points that deviate significantly, or in simpler terms are “far away”, from the rest of the data point. Outliers can be in both the univariate and multivariate forms. Univariate outliers are observations that significantly deviated values from the distribution of one variable. For example, a univariate …
Q: What is the most interesting topic in data mining?
A: – It can be referred to as the procedure of mining knowledge from data – Data mining can be defined as the procedure of extracting information from a set of the data – The procedure of data mining also involves several other processes like data cleaning, data transformation, and data integration – All of the above
Q: What is data mining and its importance?
A: Relational databases Data warehouses Transactional databases Advanced DB and information repositories – Object-oriented and object-relational databases – Spatial databases – Time-series data and temporal data – Text databases and multimedia databases – Heterogeneous and legacy databases … Traditional Techniques may be unsuitable due to