Questions tagged [density-estimation]
The construction of an estimate, based on observed data, of an unobservable underlying probability density function (pdf).
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How do I learn to relate a numerical of algorithm to its actual algorithm? Eg-: How do I relate this dbscan algorithm numerical with actual algorithm? [closed]
I have understood this numerical. I know how I calculated the clusters. But, I can't relate it with algorithm at all. Here is the algorithm-:
How do I learn to relate algorithm that I study with ...
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3answers
83 views
logistic regression or density estimation for binary dependent variable and binary (or categorical) features [closed]
I have a binary dependent variable $t$ and categorical features. We can even simplify to binary features since I can one-hot encode the categorical variables. In practice the one-hot encoding induces ...
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Why exactly KNN is outperforming Parzen by a huge margin in classificaton task
I'm trying to implement a Naive Bayes classifier, which uses either of hypercubic Parzen window or KNN to estimate a density function.
The data I'm using is Fashion MNIST. The steps I take are that ...
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0answers
22 views
MLE for Poisson conditioned on multivariate Gaussian?
I am writing some Python code to fit 2D Gaussians to fluorescent emitters on a dark background to determine the subpixel-resolution (x, y) position of the fluorescent emitter. The crude, pixel-...
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Coupling Layer in RealNVP and NICE
Why is a coupling layer called so, in NICEand RealNVP density estimation?
Does it have anything to do with the coupling of probability distributions?
What is the intuitive goal of using these layers?
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23 views
How to evaluate KDE against histogram?
I am currently testing some approaches for density estimation, and I think the basic approach of histograms may not be the best option to me and KDE is certainly a good alternative to go. While ago I ...
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Learn smoothly varying mean and variance of a variable over a 2d domain
For a problem which I am working on at the moment, I'm interested in learning how the mean and variance of some response variable y changes with two independent ...
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3answers
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How to convert regression into classification?
So I have a regression problem with bunch of features X, and labels in the amount (price $). How can I convert it to classification problem? I have read about convert label from continuous to ...
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19 views
how can i interpret kernel density plots from classification?
all,
i have a classification problem where i am predicting likelihood of client defaulting on loan. i plotted the predicted probabilities from my model, and then plotted against the label '1' for ...
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22 views
Test independence based on Kernel Density Estimation
I am working on a problem where I have a dataset of
$X$ is dataset with $(X, Y, T, K)$ four attributes, I'd like to test if $P(X, Y, T)P(K) = P(X, Y, T, K)$, that is if $X, Y, T$ is independent of $K$....
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Simple example of Parzen window (kernel density estimation)
I am confused about the Parzen Window question.
Suppose we have two training data points located at 0.5 and 0.7, and we use 0.3 as its rectangle window width. How do we estimate its probability ...
