All Questions
Tagged with nonparametric machine-learning
55
questions
4
votes
1
answer
52
views
In what ways is Gaussian Process Regression both parametric and non-parametric?
Gaussian Process Regression is considered a "non-parametric" model. However, the term "non-parametric" is often used imprecisely to mean different things, leading to questions ...
- 847
0
votes
0
answers
4
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learning guarantees for gaussian weighting of training points
I have my training data for binary classification that consists of $N$ pairs $$(x_i\in R^F, y_i \in {-1, 1})$$ $i\in [1,\dots,N]$. My classification rule of a new point $x$ is simply
$$
\hat{y}(x) = \...
1
vote
0
answers
166
views
Projection pursuit regression
Projection pursuit regression (PPR) is described in Hastie et al.'s The Elements of Statistical Learning in the chapter on neural networks. The algorithm was introduced by Friedman and Stuetzle (1981)....
- 751
0
votes
0
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7
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Regression models that conform to functional groupings of features
For example, suppose we want to predict y with features x1, x2, x3, x4. If I specify
...
- 31
5
votes
2
answers
544
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Is density estimation the same as parameter estimation?
I was studying parameter estimation from Sheldon Ross' probability and statistics book. Here the task of parameter estimation is described as follows:
Is this task the same of density estimation in ...
- 151
4
votes
3
answers
475
views
Perfect Prediction: Why Would We Ever Use a Statistical Model?
Dear statistics experts
I need your help with something that has bothered me for a while now. My problem revolves around perfect prediction and essentially boils down to:
Why would we ever set up and ...
- 69
1
vote
0
answers
39
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validation and calibration of crop yield data using conditional inference trees
I am trying to validate and calibrate the conditional inference tree model using the crop yield data, and I started by splitting my dataset into training and test sets.
After splitting, I had to ...
- 11
3
votes
0
answers
66
views
Looking for the Holy Grail of nonparametric regression
Unfortunately, to state precisely the question, I need some formal preliminaries.
Let $d \in \mathbb{N}$.
For each $d^* \in \{1,\dots,d\}$, define $\mathcal{M}_{d^*}$ be the set of probability ...
- 193
1
vote
0
answers
159
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which non parametric test to use for anomalous NN model outputs
Assume I have a bunch of trained NN models for classifying MNIST. All of them except one was trained on the same training set while the one was trianed on a different training set (could have ...
- 393
1
vote
0
answers
432
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AIPW and Cross-fitting (Stanford stat361)
I am reading lecture note (Stanford stat361: https://web.stanford.edu/~swager/stats361.pdf) written by Stefan Wager. At page 23-24 the author states dependent summands become independent after ...
- 39
3
votes
1
answer
213
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Random forest with nonnegative dependent variable
I have a modeling framework with an outcome that must necessarily be positive. In the training data, the outcome ranges from close to zero to much higher (approximately 0.05 to 100). Is there a way to ...
- 725
5
votes
1
answer
2k
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Is it possible to use variational autoencoders with Non-Gaussian data?
I am dealing with two scenarios: 1) Non-Gaussian data distribution and 2) non-stationary data).
First, I am planning to use a variational autoencoder for modeling the probability distribution of the ...
- 333
1
vote
0
answers
135
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Extraction of modes from a multi-modal density function
I am trying to extract modes from a multi-modal density function and not just peaks. For example, in the two density functions below (images), I would like to extract the curves contained in the black ...
- 303
3
votes
1
answer
329
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What is the difference between sieve estimation and structural risk minimization?
I was wondering if you could help me out. I am quite confused about the difference between sieve estimators (Ulf Grenander) and structural risk minimization (SRM) (Vladimir Vapnik). Could anyone give ...
- 131
1
vote
0
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878
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what are the main differences between parametric and non-parametric machine learning algorithms?
I am interested in parametric and non-parametric machine learning algorithms, their advantages and disadvantages and also their main differences regarding computational complexities. In particular I ...
- 11