3D head model classification using KCDA

Computer Science

• Discriminant Analysis 100%
• Classification Models 100%
• Linear Discriminant Analysis 66%
• Gaussian Assumption 66%
• Experimental Result 33%
• Feature Space 33%
• Dimensional Space 33%
• Kernel Method 33%
• Cluster Structure 33%
• Classification Problem 33%
• Multiple Cluster 33%

Engineering

• Limitations 100%
• Gaussians 100%
• Experimental Result 50%
• Feature Space 50%
• Main Idea 50%
• Dimensional Space 50%
• Classification Problem 50%
• Multiple Cluster 50%

Mathematics

• Discriminant Analysis 100%
• Gaussian Distribution 40%
• Dimensional Space 20%
• Classification Problem 20%
• Kernel Method 20%
• Feature Space 20%