Isbn: 9780471268512 - exploratory data mining and data cleaning (10 Ergebnisse)

Zustand: Very Good. Item in very good condition! Textbooks may not include supplemental items i.e. CDs, access codes etc.

Zustand: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.…

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Zustand: New. In English.

Zustand: New. pp. xii + 203 Illus.

hardcover. Zustand: Wie neu. Cover leicht berieben, minimale Lagerspuren am Buch, Inhalt einwandfrei und ungelesen Sprache: Englisch Gewicht in Gramm: 525.

Zustand: New. TAMRAPARNI DASU, PhD, and THEODORE JOHNSON, PhD, are both members of the technical staff at AT&T Labs-Research in Florham Park, New Jersey.A unique, integrated approach to exploratory data mining and data qualityData analysts at information-intensive bu.

Hardcover. Zustand: Brand New. 1st edition. 203 pages. 9.25x6.25x0.75 inches. In Stock.

Zustand: New. This reference book develops a systematic process of data exploration, data cleaning and evolving a suitable modelling strategy to help analysts determine and implement a final technique. Series: Wiley Series in Probability and Statistics. Num Pages: 224 pages, Illustrations. BIC Classification: UNC. Category: (P) Professional & Vocational. Dimension: 242 x 164 x 20. Weight in Grams: 508. . 2003. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.…

Buch. Zustand: Neu. Neuware - \* Written for practitioners of data mining, data cleaning and database management.\* Presents a technical treatment of data quality including process, metrics, tools and algorithms.\* Focuses on developing an evolving modeling strategy through an iterative data exploration loop and incorporation of domain knowledge.\* Addresses methods of detecting, quantifying and correcting data quality issues that can have a significant impact on findings and decisions, using commercially available tools as well as new algorithmic approaches.\* Uses case studies to illustrate applications in real life scenarios.\* Highlights new approaches and methodologies, such as the DataSphere space partitioning and summary based analysis techniques.Exploratory Data Mining and Data Cleaning will serve as an important reference for serious data analysts who need to analyze large amounts of unfamiliar data, managers of operations databases, and students in undergraduate or graduate level courses dealing with large scale data analys is and data mining.…