Questions tagged [multimodality]

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How to combine multiple signal data in my ML model?

I'm doing a task where I need to work with healthcare data from a few different sources. For example, one is an audio signal recording while another is biometric signal reading such as ECG. Both of ...
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2answers
37 views

Testing for uniformity of p-values with multi-modal samples

I'm working with data that is multi-modal, I need to be able to check if the individual samples are statistically distinct or not, so I'm running KS-test against pairs of samples. But I've noticed ...
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Comparing similarity of samples under time-dependant noise (KS-test for dependant samples)

I'm measuring response times of a process under different inputs and want to check if the input correlates with the response time. The problem is that the differences I'm expecting are small while ...
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1answer
20 views

Is the multimodal as in multimodal machine learning the same as that as in multimodal distribution?

The multimodal distribution is a distribution with multiple modes as shown below. It reminds me of the multimodal machine learning where multimodal implies multiple types of information, just like ...
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20 views

What is a robust distribution for truncated, multi-modal count data for use in GLM analysis?

I have a dataset consisting of observations of number of fish caught per sampling event and would like to conduct a variety GLM analyses on it using R. The maximum number of fish is capped at 75 (...
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25 views

Random Forest performed significantly better than other models for Multimodal data, Why?

Sorry about the vague question. I have multimodal human biosensory data, from eyes, body position and EEG. In my classification, Random Forest performed better than Neural Networks, SVM or Naive ...
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16 views

How can LSTM predict correctly?

i made CNN-LSTM parallel layers to predict speed and steering values. The layers look like (not the same values but similar structure) : End-to-end Multi-Modal Multi-Task Vehicle Controlfor Self-...
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21 views

Summary statistics over varied n-modal Gaussian KDEs

I am analysing a bunch of data files which represent responsiveness of cells to addition of a drug. If a drug is not added, cell responds normally, if it is added, it shows abnormal patterns: (TLDR at ...
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39 views

Finding the first tail in distribution [closed]

Pdf of a distribution is shown in the figure below. Is there a way to estimate the first tail (or) to segment first mode and its tail? he KDE plot resulted from a transaction dataset where ...
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1answer
21 views

Does the multimodal probability distribution tend toward uniform distribution as number of modes becomes very large?

Does the multimodal probability distribution tend toward uniform distribution as number of modes becomes very large? Multimodal probability density distribution is formed by the convex combination of ...
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49 views

Significance of modes in a distribution

I have several datasets with angular measurements, i.e. circular values from 0 to $2\pi$. These datasets tend to have peaks at 0 and/or $\pi$, and I need to tell if the peaks are detected/significant. ...
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3answers
167 views

Detecting if an 1-dimenisional distribution is Multimodal

I'm writing up some C++ code for one of my Master's coursework. What I'm actually doing at the moment isn't on the syllabus, but I wish to implement it anyway as it will allow me to produce my own ...
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2answers
89 views

Multi-View Survival Analysis

I have a data set containing various subsets of medical data about a cohort of patients. For example there are blood test results, demographics, medical examination results and a medical history among ...
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57 views

Is this Bayesian model averaging?

A classical example of Bayesian model averaging (BMA) is the regression setup where the choice of different sets of covariates corresponds to different models $\mathcal{M}_k$, $k = 1, \ldots, K$, ...
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1answer
58 views

Which statistical methods are best suited for distribution with two peaks?

My data shows this distribution: I am looking for a statistical distribution which my data follows. Thought about poisson distribution, but goodness of fit test shows p < 0.05
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26 views

Distinguish between underlying Distribution and data shape in data transforming?

My question is not well worded, which is part of the problem. I’m specifically trying to apply this to my understanding of Six Sigma, but it probably applies everywhere. I know that having a normal ...
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64 views

Describe why a distribution might be multimodal?

Suppose that I visualized a distirbution and noticed that it was multimodal. For example, I collected the heights of a bunch of students. I notice that the distirbution is multimodal. How would I ...
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17 views

Fastest Multimodal sampler

I am currently working with Multinest, a bayesian multimodal sampler however it becomes slow for higher dimensions, exponentially slow. Is there another sampler out there that can give me parameter ...
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1answer
162 views

Confusion about multimodal machine learning

I recently browsed through this tutorial on multimodal data. Attention: Multimodal in the sense of feature of very different type, that express the same thing -think picture and voice of ...
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75 views

Is the Latent Dirichlet Allocation topic posterior multimodal?

In fitting the Latent Dirichlet Allocation with collapsed Gibbs sampling one builds a sampled approximation to the topic posterior distribution, $P(z|w)$ and use that to calculate the topic and word ...
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0answers
37 views

Multimodality of mixtures of more than two Normal distributions

Let $$\phi(x;\mu,\sigma) = \frac{1}{\sigma \sqrt{2\pi}} \exp \left(- \frac{(x-\mu)^2}{2\sigma^2}\right)$$ denote the Gaussian density function ($\sigma > 0$). Let $$f(x) = \sum_{i=1}^N p_i \...
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40 views

How to numerically find the mode of a joint probability distribution from samples? [duplicate]

I have a large number of samples (say $N$) from a multimodal joint probability distribution, for example: ...
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354 views

Does it make sense to calculate MLE for multimodal distributions?

The simplest examples of multimodal distributions I've seen are mixtures, namely mixtures of normals. However, in this case, the Maximum Likelihood Estimator [MLE] doesn't make much sense. An example ...
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137 views

Is redundancy across different modalities required in multimodal machine learning

There are lots of articles available pertaining to 'multi-modal machine learning'. Among the major challenges, there is a one of representation i.e. "how to represent and summarize multi-modal data ...
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45 views

inverse integration of multimodal distribution

I have a probability distribution, with a number of modes with different peak values, and I have to capture the 90% most significant value ranges. My idea is to apply a threshold starting from the ...
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1answer
550 views

Evaluation of MCMC samples

My model contains five parameters. I want to make Bayesian estimation, but the Bayes estimates can not be obtained in closed form. So, I used Metropolis-Hastings to generate MCMC samples from ...
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1answer
643 views

mean variance of multimodal distribution

This may be too much of a simplistic question: but is it correct to say that it simply doesn't make sense to compute averages/means of data that is fundamentally multimodal? That is, there is not one ...
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1answer
123 views

Multimodality from unimodal variables

Let's say a data matrix $\bf{X} \in \mathbb{R}^{N \times D}$ has $D$ random variables each with $N$ observations. So $j$th column of $\bf{X}$ is $N$ observations of $j$th random variable. Suppose ...
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2answers
133 views

Is the likelihood of the sum of unimodal likelihoods also unimodal?

Let $p$ be a probability distribution and let $\mathcal{D}_1$, $\mathcal{D}_2$ be two sets of observations. If the likelihood of the parameter for some observations $$ \mathcal{L}(\theta; \mathcal{D})...
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1answer
169 views

How to detect multivariate binomial distributions?

I tried the hartigans dip test, and it works well for univariate distributions. However, when i tried taking each variable (dimension) and applied hartigans dip test (assuming that if along one ...
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2answers
640 views

Multimodal prior

In Bayesian method, a posterior can be either unimodal or multimodal. But, I cannot find any multimodal prior case yet. I wonder if it is possible, and there is any case that is using multimodal ...