Quadratic programming in plain English
The big picture is: a quadratic programming problem can be reduced to be a linear programming problem. Here is how: (1) KTT conditions For any non-linear programming: max: f(x), s.t: g(x)…
Linear programming in plain English
Why study the linear programming (LP) ? LP has a lot of use cases, one of them is the SVM ( support vector machine). The SVM ‘s Lagrangian dual can give…
Logistic regression ( classification) in plain English
In logistic regression, we just assume the probability of x to be classified as 1 is : P( y = 1 | x ) = 1 / ( 1 +…
Bayes classifier in plain english
Bayes theorem: where A and B are events and P(B) ≠ 0. P(A) and P(B) are the probabilities of observing A and B without regard to each other. P(A | B), a…
Decision tree learning in plain english
Decision tree works just like computer language if. In AI/ML world, the problem is usually like this: Given training set with features [( f1,f2 ….), ….] and known category/label [c1,…
k-Nearest Neighbors in plain English
Here is how it works in plain English: we have training set ( known features ( normalized), and classification) : many data points: [ ( feature1,feature2,feature 3,…), ( f1,f2,f3 …),…
