Tagged Questions
3
votes
1answer
113 views
Logistic regression algorithm in Ruby
I have been using R to calculate logistic regression with many independent variables for a Ruby on Rails web application. However, I can no longer import data from the database to R using RPostgreSQL. ...
1
vote
1answer
111 views
How can one show a Kmeans solution is unique?
Suppose we are given a distribution P and a constant K. We wish to minimize the kmeans objective w.r.t centers ${C1,..Ck}$:
What constraints on $P$ are known to imply that the optimal solution is ...
1
vote
1answer
130 views
How to determine if the data points are linearly separable from an SVM hyperplane
How to know the data points are linearly separable from an SVM hyperplane?
How to get the optimal classifier during iteration process?
How to calculate the complexity of the SVM model?
2
votes
1answer
216 views
Kmeans on “symmetric” data
A set is said to be fully-symmetric if for every x in it, negating one of its components results in y such that y is in the set as well.
A set is said to be semi-symmetric if for every x in it, ...
1
vote
1answer
122 views
Citation for Continuous Space Hill Climbing Algorithm pseudocode on Wikipedia?
Can anyone provide a reference for the Continuous Space Hill Climbing Algorithm pseudocode in the Wikipedia article on Hill Climbing? The Russell and Norvig text is cited, but they only provide the ...
1
vote
0answers
60 views
Root Convergence Rate of EM or MM Iteration [closed]
I have an iterative sequence for optimizing an EM/MM algorithm based loss function $L(X)$ with $t$ being the iteration number as:
$X_t=ABX_{t-1}+CX_{t-1}+X_{t-1}$ where $A$ is a diagonal matrix, $B$ ...
7
votes
1answer
429 views
How to define the termination condition for gradient descent?
Actually, I wanted to ask you how can I define the terminating condition for gradient descent.
Can I stop it based upon the number of iterations, i.e. considering parameter values for, say, 100 ...
3
votes
0answers
89 views
Scope of non-linear least squares
edit: tl;dr: I can coerce a lot of optimization problems to take the form of a non-linear least squares problem, but does it make sense to do so?
Suppose we have some empirical data $P=\{(x_i', ...
0
votes
3answers
581 views
Difference in using normalized gradient and gradient
In general setting of gradient descent algorithm, we have $x_{n+1} = x_{n} - \eta * gradient_{x_n}$ where $x_n$ is the current point, $\eta$ is the step size and $gradient_{x_n}$ is the gradient ...
2
votes
2answers
408 views
Simple, robust and fast algorithm for stochastic gradient descent
I'm trying to solve an optimisation problem with stochastic gradient descent with the following properties:
It has a very large (1,000,000+ element) parameter vector.
Empirically, there seems to be ...
5
votes
2answers
725 views
Is there an R optimization package that can handle integer constraints and non-linear objective functions?
I am looking for an optimization routine that can optimize a non-linear objective function with integer constraints. NuOPT for S-Plus, CPLEX, or Matlab include powerful optimization packages for these ...
3
votes
1answer
404 views
Effects of step size in gradient descent optimisation
Im using gradient-descent-based algorithm for my problem where
new_value = old_value - Step_size*Gradient
For exit criteria, im determining the change in fn value between iteration i.e.,
if ...
10
votes
3answers
1k views
Can someone please explain the back-propagation algorithm?
What is the back-propagation algorithm and how does it work?
