In Support Vector Machines (SVM), what is the 'Optimal Separating Hyperplane'?
In SVM, the optimal separating hyperplane is defined as the decision boundary that maximizes the margin (geometric distance) between the closest points of the opposing classes (the support vectors).
How is a standard 8-bit RGB digital color image represented computationally?
An 8-bit color image consists of three 2D color channel matrices (Red, Green, Blue) of size Height x Width, where each channel stores pixel intensities from 0 to $2^8 - 1$ = 255.
What is the key difference between a 'State Space Graph' and a 'Search Tree'?
Statements (A), (B), and (C) are all accurate distinctions between problem state graphs and algorithm search trees.
In Roger Schank's knowledge representation theories, what is a 'Script'?
Scripts organize predetermined sequences of actions in specific contexts, specifying Entry Conditions, Props, Roles, Tracks, and Scenes.
What is the 'Kernel Trick' in Support Vector Machines?
The kernel trick computes inner products in high-dimensional feature spaces where data becomes linearly separable, avoiding the computational expense of explicit coordinate transformations.