Ensuring the Robustness and Reliability of Data-Driven Knowledge Discovery Models in Production and Manufacturing

Keyphrases

• Knowledge Discovery Model 100%
• Data Reliability 100%
• Data-driven Discovery 100%
• CRISP-DM 75%
• Industry Standards 75%
• Cross-industry 50%
• Complex Data 25%
• Practical Implementation 25%
• Customizable 25%
• Data Quality 25%
• Machine Learning Models 25%
• Interdependency 25%
• Multiple Models 25%
• Multiple Data 25%
• Data Analytics 25%
• Business Knowledge 25%
• Robustness Issues 25%
• Model Improvement 25%
• Model Reusability 25%
• Data Mining Process 25%
• Data Science Framework 25%
• Quality Model 25%
• Business Objectives 25%
• Learning Analytics 25%
• Addressing Model 25%
• Address Data 25%
• Dynamic Interaction 25%
• Industry Knowledge 25%
• Model-driven Development 25%
• Data Development 25%

Computer Science

• Knowledge Discovery 100%
• Industry Standard 100%
• Data Mining 60%
• Data Analytics 20%
• Interdependency 20%
• face model 20%
• Business Objective 20%
• Dynamic Interaction 20%
• Model Development 20%
• Data Mining Process 20%
• Machine Learning Model 20%