Questions tagged [distribution]
The distribution tag has no usage guidance.
169 questions
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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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Does Double Median Absolute Deviation work for every distribution for the purpose of outlier detection?
I am using Double Median Absolute Deviation for finding outliers in a 1-D data. As mean with standard deviation gets influenced easily by outliers, that's why I chose median based approach. And the ...
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Label distribution over training, validation and test [closed]
I am wondering over whether the number of classes distributed over my training, validation, and test label affects the model.
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derivation for expected value for variance
Hi Im taking a course about probability distribution in datascience and below is derivation of the expected value for the variance
Variance = expected value of the squared difference from mean for ...
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The upper range of a collected dataset is most likely accurate, but the rest may suffer biased omissions: How to call this phenomenon?
Background: In collecting a dataset of a specific unit ordered by a numeric variable, it is possible that the upper 'cloud' of the dataset is correct, while the 'tail' seems inaccurate.
I can thus ...
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Individual models gives quite same distribution on Test set, whereas Ensembling gives better result but very different distribution
I am working on a binary classification problem with unbalanced data (17% for positive class).
The problem is as following:
My three individual models when predicting on the test set (for which I don'...
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Normalizing variables with logarithmic shape
A simple model with two variables [A,B] to train, let's say, a logistic regression or any other classification model:
A: Flat distribution from 0 to 100.
B: A logarithmic distribution from 0
to a few ...
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How to bin a distribution data reported with different frequencies ( salaries ), showing mixed linearity and non-linearity?
I am researching on pay-scales, and wish to receive advise to treat data of salaries.
Objective
My interest is to approximate the salary corresponding to different hierarchical levels in an ...
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Non-Gaussian like distributions - Classifier of source data fails on target data
I ask you for help on a classification problem (classes are represented by the numbers 0,1 and 2). All features are extracted from time series data (fundamental is sinus shape).
I have a source ...
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Normal vs Uniform Distribution for machine learning
I have a dataset that follows Zipf's law such that the majority of the values are concentrated at one end, with the remaining items containing a very small percentage. Training on the dataset as is ...
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distribution difference between image and text
Once for the task of image captioning I've read that, the features extracted from image and text by deep networks are from two different worlds and got different distribution. My question is how is ...
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A/B Testing (Binomial Distribution vs Random Distribution)
When performing an A/B test for the number of clicks for users viewing (each view is an impression) two variants of an ad, a binomial distribution can be assumed where each variant has a constant ...
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What is a distribution-wise asymmetric measure?
I was trying to understand KL-Divergence, $$D_{KL} \langle P(X) \Vert P(Y) \rangle,$$ and was going through its Wikipedia article. It says the following
In contrast to variation of information, it is ...
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How to find the best fitting parametric distribution for an empirical dataset (stock returns)?
Given some real-valued empirical data (time series), I could convert it to a histogram to have an (non-parametric) empirical distribution of the data, but histograms are blocky and jagged.
Instead, I ...
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Normal distribution and Random Forest
I have big table in dataframe (600k rows) which has y column (the variable I want to predict) and other 4 other columns that are the X.
I have run RF regressor and I got score of 0.87 when I run it ...
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How to generate a random sample and distribute values based in an probability distribution?
I want to generate a random sample based on this probability distribution:
The line is the KDE of the histogram.
My random sample will have n values, the value is ...
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How to find a probability distribution the parameters of which do not impact each other like mean and variance in normal distribution do?
I need to find a probability distribution to fit my data. My data has two important features, duration and activity count. Duration means how long one sequence lasts and activity count means the ...
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How to interpret KDE distribution graph?
I would like to know how to interpret this distribution graph. I have been doing an exercise from the book called 'Python for Finance Cookbook' by Eryk Lewinson. It does not give an in-depth ...
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[under/over]-sampling teaches model the wrong distribution?
TLDR: Will under/oversampling during the training phase teach the model the wrong distribution and adversely affect accuracy?
Let us assume you want to train a classifier to differentiate between ...
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Unable to transform the variable to normal distribution
I have a variable called 'list_price' in my data ,which is not normally distributed.
Here is the screenshot of how the distribution looks like before transformation
Tried transforming it with the ...
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Getting a balanced sample across many variables
Let’s say each element in my population has several attributes.
Let’s call then A, B, C, D, E, F.
Let’s say, for simplicity, each attribute has 10 values (but could be any number between 2 and 30).
...
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Finding the worst affected industry due to COVID in terms of unemployment
My goal is to find the worst affected industries from COVID—19 in terms unemployment.
In terms of the data I will use for this task, I have a time series county-wise unemployment rate data of each ...
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Can the extent of variability within a dataset be reflected through clustering?
As an example: I need to compare the extent of variability amongst houses belonging to 4 different architectural eras - I want to see how different the houses are within each group and then compare ...
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What is the distribution of the goal feature in this dataset
https://www.kaggle.com/kemical/kickstarter-projects
I was checking the distribution of the "goal" feature in this 2016 KickStarter data set. I figure goal would be more normally distributed ...
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A good machine learning approach for distribution of a whole?
So I had done with different classification, regression and clustering approaches for predictions of values etc. I was wondering if there is a machine learning approach for distribution of a whole ...
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Naive Bayes vs Full Bayes model classifiers
I have a hard time to understand when Naive Bayes works better than Full Bayes.
In general, i know that naive bayes does the assumption that features are independent given the class. However, if ...
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The tag on feature-scaling says "zero mean" and unit variance. Is it correct?
The tag on feature scaling says:
Popular feature scaling types include scaling the data to have zero
mean and unit variance, and scaling the data between a given minimum
and maximum value.
It is ...
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Understand how to simulate a statistics [closed]
This solution describes how to simulate statistics to find a confidence interval.
A journalist called 1000 people in town to ask who will they be voting for out of candidates A and B.
The observed ...
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How to draw a sample from data set with respect to a given categorical or numerical variable based on given freely chosen distribution? (Python)
Say I have a data set for some past period. Now new data appears and for a given variable in the data and we find that the distributions have shifted (for example with "age" it would be that suddenly ...
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Professionals appear to interpret sample correlation (e.g. Karl Pearson) as if it represents linear correlation. Is it the correct interpretation? [closed]
I am stressed following the wrong interpretation. What is the correct way of understanding a correlation coefficient.
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Compare the variances of two categorical distributions in a repeated measure design
I ran two model-building procedures with different parameters on the same sample and obtained the selection of my optimized hyperparameter for each outer fold (each of the analyses had 100 outer folds ...
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Text data distributions comparison
I would like to know what is the best method to compare the different text data distributions. I am working on text classification. I built a model using the old dataset. Now, I would like to know, ...
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How is the E(X) of a Poisson distribution lambda? [closed]
I was recently learning about the Poisson distribution, and was very perplexed about the E(X) equaling lambda. Like how did lambda even come into the picture here, isn't it a symbol of wavelength?
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Is there a cost associated with converting Koalas dataframe to Spark dataframe?
I know that pandas works "under the hood" with numpy arrays stored in dictionaries. In contrast, Koalas works with the underlying Spark framework. Does that mean that there is no extra cost associated ...
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How to resample one dataset to conform to the distribution of another dataset?
I have two datasets with 20 features, but with different feature distributions (DS_A and DS_B). How can I sample the DS_A to make its distribution similar to DS_B, with respect to multiple features??
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How to interpret axis of Histogram and distribution curve?
After doing statistical analysis of data I got the below figures:
The data contains a line length in meters which is represented with Line(m). The purpose here is to confirm the distribution behavior ...
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difference btw data distribution and frquency distribution
I have a dataset with 'n' features and corresponding labels(binary in nature). How can I calculate the data distribution and frequency distribution of the same? What is the difference btw the two?
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Calculate marginal probability distributions of a dataset
I have a dataset with 'n' features and a label(binary) corresponding each entry. I am using a predicitive model to predict these labels using those 'n' features. Now, I wish to know the marginal ...
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Confidence value for face recognition
In the context of face recognition I have the following histogram:
blue bins count the comparison distances for "self matches" (comparing two images of the same person). Orange bins count the ...
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Synthetic time series generation according to some distribution
I'm trying to develop a change detection model that uses sliding windows. Given a time series with some features I've a sliding widows that analyses that time period and compares with a successive ...
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SQL Oracle - Excel's BETAINV function (Inverse cumulative function of a beta distribution) in SQL Oracle [closed]
Is there a function equal to Excel's BETAINV(probability,alpha,beta,[A],[B]) in Oracle SQL Developer? Or a similar one which I could use to return the inverse cumulative distribution function of a ...
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Testing for gender composition between groups
I did kmeans with k=4 and I would like to find out if there are any differences in the composition of gender between the 4 clusters.
Do I use Fisher's Exact Test of Independence? Is there any ...
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evaluation metrics for multiple values per session
I have an application that executes my foo() function several times for each user session. There are 2 alternate algorithms that I can implement as ...
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Regression: How to deal with positive skewness in continuous target variable
I'm working on a regression problem. My aim is to "learn" the distribution of a continuous target $y$ as good as possible to make predictions. My model looks like:
$$y_i=\beta X_i + u_i.$$
$y$ is ...
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Univariate Outlier Detection
Let's say I have a dataset with the following format:
customerid
product
orders_in_last7days
orders_in_last6days
orders_in_last5days
orders_in_last4days
orders_in_last3days
orders_in_last2days
...
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How to estimate the marginal distribution of a class with respect to one predictor in a classification task?
I have a dataset with a binary dependent variable $y \in \{0,1\}$ and a set of predictors $x1,x2,..,t$. Here, $t$ is the time in minutes (in 24 hrs, that is $t \in (0,1440)$). I want to estimate the ...
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Generating random numbers from best probability distributions?
I have done some statistical distributions on real-world data. The distribution fitting gives me the below results (lognormal fits the best on data based on chi-squared test):
...
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How to set and check normal distribution on a data set?
Sorry if my question is simple, I have a data set with two class and want to check and set normal distribution on it(if it was necessary, in MATLAB).
But the question is that I should use it on every ...
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