# SVM and Log Regression (Log R)

## Difference between SVM and Log R?
http://www.cs.toronto.edu/~kswersky/wp-content/uploads/svm_vs_lr.pdf

## What does LogR give ? 
Posterior probability (P(y|x))

## Does SVM give any probabilistic output?
http://www.cs.cornell.edu/courses/cs678/2007sp/platt.pdf


## What are the support vectors in SVM?
The vectors that define the hyperplane (margin) of SVM.

## Evaluation of LogR?
You can use any evaluation metric such as Precision, Recall, AUC, F1.

## How does a logistic regression model know what the coefficients are?
http://www-hsc.usc.edu/~eckel/biostat2/notes/notes14.pdf

# Expectation-Maximization

## How's EM done?
https://stackoverflow.com/questions/11808074/what-is-an-intuitive-explanation-of-the-expectation-maximization-technique

## How are the params of EM updated?
https://stackoverflow.com/questions/11808074/what-is-an-intuitive-explanation-of-the-expectation-maximization-technique

## When doing an EM for GMM, how do you find the mixture weights?
I replied that for 2 Gaussians, the prior or the mixture weight can be assumed to be a Bernouli distribution.
http://www.aishack.in/tutorials/expectation-maximization-gaussian-mixture-model-mixtures/

## If x ~ N(0,1), what does 2x follow?
N(0,2)
https://en.wikipedia.org/wiki/Sum_of_normally_distributed_random_variables

## How would you sample for a GMM?
http://www.robots.ox.ac.uk/~fwood/teaching/C19_hilary_2013_2014/gmm.pdf

## How to sample from a Normal Distribution with known mean and variance?
https://stats.stackexchange.com/questions/16334/how-to-sample-from-a-normal-distribution-with-known-mean-and-variance-using-a-co