Questions tagged [distribution]
The distribution tag has no usage guidance.
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What can I do when validation data and test data has different distribution in imbalance classification?
I am building classification model for bio (scRNA) data. Datasets in this field, for example, dataset A has 1, 2 classes, dataset B has 2, 3 classes kind of that. So I integrated datasets for training ...
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Bayesian Linear regression for non-gaussian distribution
Which distribution should be considered for non-gaussian distribution while building Bayesian Linear regression. I am trying to build this model using Pymc3 library but since I have just started to ...
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Grouped Time Restricted Demand Regression with value cap
so I am working on quite an interesting regression task that I haven't encountered before.
Our company sells products (steel) in tons. We offer contracts where the customer orders a certain amount of ...
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126
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What is a good metric for comparing a single value to a distribution?
I'd like to compare single values from one distribution to another distribution, effectively transforming the second distribution in such way, that its values reflect both datasets simultaneously, i.e....
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What distribution-shift datasets exist for ML?
What datasets there are which contain a (labelled) distribution shift or which distribution-shifted datasets share classes?
Currently I have found some interesting results using CIFAR10 and the ...
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Train neural network to predict multiple distributions
I aim to train a neural network to predict 2 distributions (10 quantiles, i.e. deciles) at 5 time points. So my y is of shape:
...
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Using neural networks to learn total distributions from linearly transformed samples
I am trying to explore the use of neural network based models to replace a cumbersome challenge with a faster more approximate method. The problem involves learning a distribution termed the "...
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Intuition behind Jensen Shannon divergence between deep features of two images?
Jensen Shanon divergence is mainly used to determine the divergence between two probability distributions. Can it be used to calculate the difference between the deep feature vectors of two images?
I ...
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Use of t_family distribution in glmmTMB
I was wondering if anyone has an opinion on this question.
https://stats.stackexchange.com/q/617065/388946
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Fit a bimodal histogram with a mixture Model that is not Gaussian
I am attempting to fit with Python a histogram which presents a bimodal distribution. For now, I have tested to use the Gaussian Mixture Model (GMM) from Scikit-Learn, but I want to try with different ...
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For standard deviation's formula, why does division by sample size come before square rooting?
Why is this used to calculate a sample's standard deviation:
$s=\sqrt{\frac{1}{N-1}\sum_{i=1}^N(x_i-\bar{x})^2}$
and not something like:
$s=\frac{1}{N-1}\sqrt{\sum_{i=1}^N(x_i-\bar{x})^2}$
I ...
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Normalizing flows with truth values?
I am interested in using normalizing flows to map to a certain distribution of points, but I want to make sure that the distribution is not just of the correct general shape, but also that specific ...
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Distribution check - different results using plt.hist and seaborn.displot
I have an apparently very simple task: checking the distribution of values contained in an array data. Only thing is, I get two completely different results by ...
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Understanding Syntactic divergence
I am trying to read a paper https://arxiv.org/abs/2004.14444 Section 6.1 of the paper describes Syntactic divergence. I have confusion regarding the distribution graphs and split of the dataset.
If a ...
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What is the difference between Covariate Shift, Label Shift, Concept Shift, Concept Drift, and Prior Probability Shift?
As a beginner in MLOps, I was overwhelmed by some confusing definitions.
As far as I understand, when we have a classifier or regressor with y = f(X) function:
<...
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Strange behaviour around zero for predicted distributions from a deep learning regression model
Can somebody help make sense of these very odd distributions that I obtained from my trained deep learning regression model?
The model was trained with either MAE or MSE loss, which is what the ...
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What is the next after finding best distribution for my data?
I found the distribution of my data with "distfit" library for python. But what now? The best distribution that describes my data is "weibull" distribution. But I don't know what ...
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Multiclass classification (gradient boosted trees) predictions distribution using softmax()
Let's consider a multiclass problem where the target is composed by 20% class 'A', 50% of class 'B' and 30% of class 'C'.
The model is trained and then the class predictions are obtained via the ...
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Compute the pdf from pandas kde
I have data (features/targets in machine learning terminology), e.g. X1(t), X2(t), ... XN(t) and dependent variable y(t). I can use pandas to plot the kde's of the independent variables (X1(t),...).
I ...
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How can I obtain the mean of a Poisson distribution given the first improbable point of the distribution?
I generated a Poisson distribution with mean equal to 3 and 10000 samples by using np.random.poisson(3,10000). The plot is the following:
from this plot I see that ...
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Task Distribution
I would like to distribute tasks (going to companies and signing a deal) to sales representatives based on some condition like company location (is it near the representative's place) or profit of the ...
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name of log(n+1) plot
I am trying to plot a distribution of positive integers which contains a lot of variance. I opted to use the log of the y-values but that causes issues due to the inclusion of zeros. I though of ...
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How to plot categorical variables with a pie chart
I am concerned with a single column (fruit) from my df:
...
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How can PCA be distributed among workers?
I want to distribute the work from PCA among a set of workers.
So let samples $x_1,... , x_d\in \mathbb{R}^n$ be samples. Then to find a dimension reduction subspace we need
covariance matrix $cov(\...
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How does factoring probability distributions help?
I'm trying to make sense of machine learning and am reading Deep Learning by Goodfellow, Bengio and Courville. In section 3.14 they show an example of factoring a distribution then say "These ...
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How to measure statistical similarity or discrepancy between a dataset and a distribution?
Is any way to measure statistical similarity or discrepancy between a dataset and a distribution? I have do some research, but find most of method are intended to describe discrepancy between data and ...
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Is it possible to find an internal event in a Classification between two classes?
I am very new to the machine learning area. So my question might be trivial
I have two classes $U, V$ of binary vectors. In the training phase,
I use $u_1,\ldots, u_{1000}$ from $U$ class and $v_1, \...
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71
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Function for KDE-style distribution generation for sampling
I have some points in pytorch and I would like to sample from a distribution that resembles these points. I noticed that the seaborn kde plots seem to draw out/define a distribution graphically and I ...
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What thought processes do people use for generating priors on a variable's probability distribution?
Example
Consider a block of text with a variety of sentence types within it, of which there are 7. Within a text these sentences will be more or less likely to appear, dependent on where in the text ...
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Handling gaps in regression model
I'm facing a regression problem where I'm supposed to predict the delay of some trains. There's some peculiar particularity, however: a train is not considered delayed until it has more than 10 mins ...
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Comparing distributions Python
I have a larger dataset (random variable) 'x' containing values approximating a Gaussian distribution. From 'x', a much smaller random variable 'y' is sampled without replacement. I want to compare ...
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Probability notation q(y) and q(Y) and its implication to vector functions
The function in question is (from Appendix B, Proof of proposition 2.1 from Posterior Regularization for Structured Latent Variable Models):
$$q(\textbf{Z}) = \frac{p_{\theta}(\textbf{Z}|\textbf{X})...
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Does t-test require Standard Deviation of sample for calculation
Might be a novice question, but the main difference between a t-test and z-test, I was able to understand, is that the z-test calculation requires the SD value of the population where as in a t-test, ...
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Normalizing Distributions for features in predicting
Should features used for predictions be normalized if they are highly skewed. Or should I only normalize target feature that is supposed to be predicted?
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How to do ? serious skewed right transformations normally distribution
My target is doing two-way Anova. But Here is some problem.
This is my data like
I try log(X). Looks like a normal distribution. But try Kolmogorov-Smirnov prove is not.
Can anyone recommend another ...
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527
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Analysis of probability distribution of each features and Machine Learning
While I know that probability distributions are for hypothesis testing, confidence level constructions, etc. They definitely have many roles in statistical analysis.
However, it is not obvious to me ...
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Is there a way to create a continuous distribution graph from discrete percentiles?
I have an underlying distribution that I know is 1-tailed (Packet Response time), but the service that runs the benchmark is opaque to me. It only returns a percentile table up to some number of nines ...
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Distribution of text data
How can I identify whether the training data and test data came from same distribution or not?
I tried with TFIDF and cosine similarity
...
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Measuring the distance between data points based on mutual linkages
How to measure the distance between two data points (or: nodes?) based on their mutual share of linkages?
I don't know the technical term for that, so here is a fictitious example from scientific ...
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How to find the distribution of a single variable based on population distribution
I am trying to find the age distribution of the subset of married people of a population. However, I realise that just visualising the married count by age (Figure 1) is highly dependent on the ...
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Distribution Shift vs Transfer Learning
Transfer learning (TL) is a research problem in machine learning (ML) that focuses on storing knowledge gained while solving one problem and applying it to a different but related problem [1]
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How to generate a positive skewed array?
As the title suggests, I would like to specify the task that I really need help with:
Given three possible distributions of an array:
I know that given a skewed dataset (the left and the right), then ...
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A feature is still right-skewed after log scaling. How should it be normalized for machine learning?
I've attached two images below of a heavily right-skewed feature - call it x. I log scaled x, but it is still right-skewed and ...
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Check if distribution per week is the same
I have sales by customer (b2b) and by date. I want to check if the distribution per day inside weeks remains the same from week to week.
Initial dataset
Customer
Date
Sales
Alpha
2019-02-23
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Criteria for assessing difficulty of a question
I have a list of questions and how many times they have been answered correctly and incorrectly. Based on this, I applied the formula:
...
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Testing a Binary Classifier
I have been training a binary multilayer perceptron on a database made out of roughly 3600 0 values, and 4 1 values. Afterwards, I'm testing the MLP on a test set made out of 7 0 values and 7 1 ...
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Estimating the (normal?) distribution of the grayscale values of a region in camera footage
The problem:
Given a small ($25\times25$) region on a $1080$p image extracted from camera footage of a railway system, I am trying to detect whether there is a train present or not. I proceed to take ...
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Non IID variables and SVM Classifier
I am training an SVM model to predict the trend of stock prices (one-day ahead predictions. Classification task). It Had completely slipped from my mind that SVMs assume IID data until I had a ...
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Data Analytics how to read ECDF graph
Hi there, My question is about how to read ECDF graphs. I am still quite unsure what the jumps / zig-zags in the graph mean and what is happening when there is a horizontal line and so on. I would be ...
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718
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How to make a gaussian distribution in python considering mean. variance. skewness and kurtosis?
np.random.normal(mean,sigma,size) allows to create a gaussian distribution based only on mean and variance. I want to create a distribution based on ...
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