Data Mining and Machine Learning Applications. Группа авторов
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19 15 Classification of EEG Signals for Detection of Epileptic Seizure Using Restricted Boltzmann Machine Classifier 15.1 Introduction 15.2 Related Work 15.3 Material and Methods 15.4 Experimental Framework 15.5 Experimental Results and Discussion 15.6 Discussion 15.7 Conclusion References
20 16 An Enhanced Security of Women and Children Using Machine Learning and Data Mining Techniques 16.1 Introduction 16.2 Related Work 16.3 Issue and Solution 16.4 Selection of Data 16.5 Pre-Preparation Data 16.6 Application Development 16.7 Use Case For The Application 16.8 Conclusion References
21 17 Conclusion and Future Direction in Data Mining and Machine Learning 17.1 Introduction 17.2 Machine Learning 17.3 Conclusion References
22 Index
List of Illustrations
1 Chapter 1Figure 1.1 Knowledge discovery in Database—KDD.Figure 1.2 Time series database.Figure 1.3 Data warehouse.Figure 1.4 Decision Tree.Figure 1.5 Installation of KNIME.Figure 1.6 Installation of KNIME (2).Figure 1.7 Setting path for installing KNIME.Figure 1.8 Starting installation of KNIME.Figure 1.9 Selecting directory as a workspace.Figure 1.10 Starting KNIME.Figure 1.11 Completing setup wizard.Figure 1.12 Installing Workspace in KNIME.Figure 1.13 Installing KNIME (2).Figure 1.14 Specifying memory for KNIME.Figure 1.15 Finalizing the installation of KNIME.Figure 1.16 Initial screen of KNIME.
2 Chapter 2Figure 2.1 Process of mining data stream.Figure 2.2 Sample of graph data set.Figure 2.3 Multi-source & multidimensional information.Figure 2.4 Shows the data mining process of multimedia data.Figure 2.5 Mining of multimedia data.Figure 2.6 Shows social media mining.Figure