305,57 €
359,49 €
-15% su kodu: ENG15
Knowledge-Oriented Applications in Data Mining
305,57 € 
- Išsiųsime per 10–14 d.d.
The progress of data mining technology and large public popularity establish a need for a comprehensive text on the subject. The series of books entitled by 'Data Mining' address the need by presenting in-depth description of novel mining algorithms and many useful applications. In addition to understanding each section deeply, the two books present useful hints and strategies to solving problems in the following chapters. The contributing authors have highlighted many future research direction…
305.57
2025-07-20 23:59:00
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- Leidėjas: IntechOpen
- ISBN-10: 9533071540
- ISBN-13: 9789533071541
- Formatas: 17 x 24.4 x 2.5 cm, kieti viršeliai
- Kalba: Anglų
- Extra -15 % nuolaida šiai knygai su kodu: ENG15
Knowledge-Oriented Applications in Data Mining + nemokamas atvežimas! | knygos.lt
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The progress of data mining technology and large public popularity establish a need for a comprehensive text on the subject. The series of books entitled by 'Data Mining' address the need by presenting in-depth description of novel mining algorithms and many useful applications. In addition to understanding each section deeply, the two books present useful hints and strategies to solving problems in the following chapters. The contributing authors have highlighted many future research directions that will foster multi-disciplinary collaborations and hence will lead to significant development in the field of data mining.EXTRA 15 % nuolaida su kodu: ENG15
305,57 €
359,49 €
Išsiųsime per 10–14 d.d.
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Nuolaidos kodas galioja perkant nuo 10 €. Nuolaidos nesumuojamos.
- Leidėjas: IntechOpen
- ISBN-10: 9533071540
- ISBN-13: 9789533071541
- Formatas: 17 x 24.4 x 2.5 cm, kieti viršeliai
- Kalba: Anglų
The progress of data mining technology and large public popularity establish a need for a comprehensive text on the subject. The series of books entitled by 'Data Mining' address the need by presenting in-depth description of novel mining algorithms and many useful applications. In addition to understanding each section deeply, the two books present useful hints and strategies to solving problems in the following chapters. The contributing authors have highlighted many future research directions that will foster multi-disciplinary collaborations and hence will lead to significant development in the field of data mining.
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