
Applied Intelligent Decision Making in Machine Learning
Description
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To address these objectives, this edited book includes a dozen chapters contributed by authors from around the globe. The authors attempt to solve these complex problems using several intelligent machine-learning techniques. This allows researchers to understand the mechanism needed to harness the decision-making process using machine-learning techniques for their own respective endeavors.
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Persons
Jitendra Kumar Rout is an Assistant Professor in School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, India.
Suresh Chandra Moharana is an Assistant Professor in School of Computer Engineering at KIIT Deemed to be University.
Nilanjan Dey is an Assistant Professor in Department of Information Technology at Techno India College of Technology (under Techno India Group), Kolkata, India.
Content
2. Decoding Common Machine Learning Methods: Agricultural Application Case Studies Using Open Source Software.
3. A Multi-Stage Hybrid Model for Odia Compound Character Recognition.
4. Development of Hybrid Computational Approaches for Landslide Susceptibility Mapping Using Remotely Sensed Data in East Sikkim, India.
5. Domain-Specific Journal Recommendation Using Feed Forward Neural Network.
6. Forecasting Air Quality in India through an Ensemble Clustering Technique.
7. Intelligence-Based Health Biomarker Identification System Using Microarray Analysis.
8. Extraction of Medical Entities Using Matrix-Based Pattern-Matching Method.
9. Supporting Environmental Decision Making: Application of Machine Learning Techniques to Australia's Emissions.
10. Prediction Analysis of Exchange Rate Forecasting Using Deep Learning-Based Neural Network Models.
11. Optimal Selection of Features Using Deep Learning-Based Optimization Algorithm for Classification.
12. An Enhanced Image Dehazing Procedure Using CLAHE and Guided Filter.
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