Questions tagged [density-estimation]
The construction of an estimate, based on observed data, of an unobservable underlying probability density function (pdf).
10
questions
0
votes
0answers
8 views
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?
1
vote
0answers
22 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 ...
1
vote
0answers
12 views
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 ...
0
votes
3answers
1k views
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 ...
0
votes
1answer
18 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 ...
0
votes
0answers
71 views
Evaluation of Mixture Density Networks
I have programmed an Mixture Density Network model to a market price. As input I have many numerical and categorical properties. The output of the network is a probability distribution (shape, ...
0
votes
0answers
20 views
Efficiently estimating the number of clusters in a dataset
Let's assume that I have a high-dimensional dataset and the true number of clusters is quite high (let's say 200 or 300). Are there ways to estimate this number efficiently?
I am well aware of the ...
0
votes
0answers
15 views
Using kernel estimation to find similarity/difference between two feature sets for binary classification
I am trying to train a binary classifier using word vectors. I have the tfidf vectors for each sentence in my training set. Before applying binary classification algorithms, I just want to check ...
1
vote
0answers
17 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 $K$....
1
vote
1answer
3k views
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 ...
