All Questions
Tagged with nonparametric machine-learning
54
questions
1
vote
1
answer
236
views
Kernel nonparametric regression
One of the methods for nonparametric regression is using kernels.
My question is what are the conditions on the kernels functions in this method?
In other words how can I decide if a given function ...
- 109
0
votes
1
answer
30
views
How to compute the unconditioned density in $1NN$ classier?
Suppose I have $50$ training points $x_1$, $x_2,\ldots,x_{50}$ and they are distributed via bimodal Gaussian on real line. Now, given a new point, for $1NN$, I am trying to find a interval around $x$ ...
- 210
53
votes
9
answers
3k
views
Are all models useless? Is any exact model possible -- or useful?
This question has been festering in my mind for over a month. The February 2015 issue of Amstat News contains an article by Berkeley Professor Mark van der Laan that scolds people for using inexact ...
- 20.8k
1
vote
0
answers
124
views
What are some examples of applied machine learning problems that requires using mixed models?
What are some examples of applied machine learning problems that requires using mixed models? I'm just introduced to the notion of mixed models. As I understand it, it is a combination of parametric ...
- 737
4
votes
1
answer
2k
views
Friedman's test to identify best of multiple classifiers on multiple domains
I have several classifiers $f_i\ (i=1, \cdots, N)$ and calculated performance measures on multiple domains $(D)$ for each. Thus, there are $N \times D$ values.
I want to find out (increasing ...
- 599
7
votes
1
answer
309
views
Kendall-tau and RKHS spaces
Given two random variables $X_1$ and $X_2$, the Kendall-tau correlation coefficient could be defined as $$ \tau(X_{1},X_{2})=\mathbb{P}\Big((X_{1}-\tilde{X}_{1})(X_{2}-\tilde{X}_{2})>0\Big)-\mathbb{...
- 171
4
votes
1
answer
133
views
Learning parameters of non-parametric Bayesian models
I have a sample of Chinese restaurant process which I want to model as Pitman–Yor process. How do I determine parameters of Pitman-Yor model from given sample?
For Dirichlet process I would just use ...
- 389
10
votes
2
answers
1k
views
Best methods of feature selection for nonparametric regression
A newbie question here. I am currently performing a nonparametric regression using the np package in R. I have 7 features and using a brute force approach I identified the best 3. But, soon I will ...
- 101
37
votes
4
answers
49k
views
What is the weak side of decision trees?
Decision trees seems to be a very understandable machine learning method.
Once created it can be easily inspected by a human which is a great advantage in some applications.
What are the practical ...
- 1,412