#	Table of Content
1	Classification and Regression Tree (CART) Theory
1.1	History of CART
1.2	Machine Learning (CART)
1.3	Classification versus Regression
1.4	Umbrella of CART
1.5	Roots of our LNOB trees
2	ESCAP LNOB Trees
2.1	LNOB tree specifications
2.2	Indicators, Response Variables
2.3	Circumstances, Independent Variables
2.4	Source of data
2.5	LNOB Tree Example
2.5.1	LNOB Branches
2.5.2	LNOB Nodes
2.5.3	Furthest ahead group
2.5.4	LNOB Terminal nodes
2.5.5	Furthest behind group
2.6	Feature Space Diagram
2.6.1	All data points
2.6.2	1st split
2.6.3	2nd split
2.6.4	3rd split
2.7	LNOB Trees vs. Feature Space Diagram
2.8	Furthest behind group in a Feature Space Diagram
2.9	Furthest behind group in an LNOB Tree
2.10	Pros and cons of LNOB Trees
3	Dissimilarity Index
3.1	Origins of D-Index
3.2	D-index Scale
3.3	Video on D-Index
3.4	D-Index formula
3.4.1	Number of groups
3.4.2	Calculating number of groups
3.4.3	Country average access rate
3.4.4	Group access rate
3.4.5	Weighted sampling of group
3.4.6	Example of calculating D-Index
3.5	D-Index and barriers

Furthest behind group in a Feature Space Diagram

Here we see our furthest behind intersect between the Bottom 40% of household wealth and lower educated. And our furthest ahead are composed solely of the top 60% of household wealth.

Introductory training

Furthest behind group in a Feature Space Diagram

An Introduction to the Leaving No One Behind (LNOB) Analysis

An Introduction to the Leaving No One Behind (LNOB) Analysis

An Introduction to the Leaving No One Behind (LNOB) Analysis

An Introduction to the Leaving No One Behind (LNOB) Analysis

An Introduction to the Leaving No One Behind (LNOB) Analysis