| Description |
1 online resource |
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text file rda |
| Contents |
Cover; Copyright; Credits; About the Author; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Installing and Using KNIME; Few words about KNIME; Installing KNIME; Installation using the archive; KNIME for Windows; KNIME for Linux; KNIME for Mac OS X; Troubleshooting; KNIME terminologies; Organizing your work; Nodes; Node lifecycle; Meta nodes; Ports; Data tables; Port view; Flow variables; Node views; HiLite; Eclipse concepts; Preferences; Logging; User interface; Getting started; Setting preferences; KNIME; Other preferences; Installing extensions; Workbench. |
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Workflow handlingNode controls; Meta nodes; Workflow lifecycle; Other views; Summary; Chapter 2: Data Preprocessing; Importing data; Importing data from a database; Starting Java DB; Importing data from tabular files; Importing data from web services; REST services; Importing XML files; Importing models; Other formats; Public data sources; Regular expressions; Basic syntax; Partial versus whole match; Usage from Java; References and tools; Alternative pattern description; Transforming the shape; Filtering rows; Sampling; Appending tables; Less columns; Dimension reduction; More columns. |
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GroupByPivoting and Unpivoting; One2Many and Many2One; Cosmetic transformations; Renames; Changing the column order; Reordering the rows; The row ID; Transpose; Transforming values; Generic transformations; Java snippets; The Math Formula node; Conversion between types; Binning; Normalization; Text normalization; Multiple columns; XML transformation; Time transformation; Smoothing; Data generation; Generating the grid; Constraints; Loops; Workflow customization; Case study -- finding min-max in the next n rows; Case study -- ranks within groups; Summary; Chapter 3: Data Exploration. |
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Computing statisticsOverview of visualizations; Visual guide for the views; Distance matrix; Using visual properties; Color; Size; Shape; KNIME views; HiLite; Use cases for HiLite; Row IDs; Extreme values; Basic KNIME views; The Box plots; Hierarchical clustering; Histograms; Interactive Table; The Lift chart; Lines; Pie charts; The Scatter plots; Spark Line Appender; Radar Plot Appender; The Scorer views; JFreeChart; The Bar charts; The Bubble chart; Heatmap; The Histogram chart; The Interval chart; The Line chart; The Pie chart; The Scatter plot; Open Street Map; 3D Scatterplot. |
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Other visualization nodesThe R plot, Python plot, and Matlab plot; The official R plots; The RapidMiner view; The HiTS visualization; Tips for HiLiting; Using Interactive HiLite Collector; Finding connections; Visualizing models; Further ideas; Summary; Chapter 4: Reporting; Installation of the reporting extensions; Reporting concepts; Importing data; Sending data and images to a report; Importing from other sources; Joining data sets; Preferences; Using the designer; In visible views; Report properties; Report items; Label; Text; Dynamic text; Data; Image; Grid; List; Table; Chart; Cross Tab. |
| Summary |
KNIME Essentials is a practical guide aimed at getting the results you want, as quickly as possible.""Knime Essentials"" is written for data analysts looking to quickly get up to speed using the market leader in data processing tools, KNIME. No knowledge of KNIME is required, but we will assume that you have some background in data processing. |
| Bibliography |
Includes bibliographical references and index. |
| Language |
English. |
| Subject |
Data mining.
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Open source software.
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Data Mining |
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Exploration de données (Informatique) |
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Logiciels libres. |
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COMPUTERS. |
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General. |
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Data mining |
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Open source software |
| Other Form: |
Print version: 9781299999121 |
| ISBN |
1299999123 (electronic bk.) |
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9781299999121 (electronic bk.) |
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9781849699228 (electronic bk.) |
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1849699224 (electronic bk.) |
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