Hybrid features prediction model of movie quality using Multi-machine learning techniques for effective business resource planning

Keyphrases

• Accuracy Measure 20%
• Arts-based Methods 20%
• Bagged Tree 60%
• Boosted Tree Classifier 40%
• Boosted Trees 20%
• Business Interests 20%
• Business Outcomes 20%
• Classification Model 40%
• Decision Tree 40%
• F-measure 20%
• Feature Prediction 100%
• Feature-based 40%
• Hybrid Features 100%
• Least Squares Support Vector Machine 20%
• Linear Kernel 20%
• Logistic Regression 40%
• Machine Learning Algorithms 20%
• Machine Learning Classification 40%
• Machine Learning Techniques 100%
• Movie Industry 20%
• Movie Quality 100%
• Movie Success 20%
• Multi-machine 100%
• Multiple Machines 20%
• Performance Measures 20%
• Precision Measure 20%
• Precision-recall 20%
• Prediction Model 100%
• Principal Coordinate Analysis (PCoA) 20%
• Proposed Work 20%
• Quadratic Kernel 20%
• Quality Prediction 20%
• Quality Prediction Model 60%
• Recall Measures 20%
• Release Dates 20%
• Resource Planning 100%
• Social Media Data 40%
• Support Vector Machine 20%
• Tree Support 20%

Computer Science

• Analysis Technique 16%
• Classification Models 33%
• Decision Tree 33%
• Experimental Result 50%
• Influencing Factor 16%
• Learning System 33%
• Logistic Regression 33%
• Machine Learning 33%
• Machine Learning Algorithm 16%
• Machine Learning Technique 100%
• Multiple Machine 16%
• Performance Measure 16%
• Prediction Model 100%
• Principle Component Analysis 16%
• Social Medium Data 33%
• Support Vector Machine 66%