All Questions
Tagged with clustering regression
95 questions
0
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31
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Missing values in data set before DBSCAN
My goal is to identify bots and fraudulent users for an application. Ideally, this would be a regression problem where users are rated on a continuous scale. I have 4 tables that cover different ...
- 1
0
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0
answers
17
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Diagnostic checks before and after adjusting for standard errors in R
Currently, I'm fitting a regression model for my dataset. As there are clusters, I refitted the model using the coeftest() function from the ...
- 227
4
votes
3
answers
351
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Outlier detection methods aware of target variable
I am trying to predict ambulance demand for the next hour, for a city area in the USA, based on previous demand, weather, large people gatherings, and similar spatio-temporal factors.
I have noticed ...
- 61
2
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1
answer
91
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Is certain data better for Fixed effects compared to Mixed effects?
I think it is an obvious question with an obvious answer, but I want to confirm.
In hierarchical regression models, if some clusters have very few observations, the coefficients for those clusters ...
0
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0
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54
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Weighted regression with no variance within cluster
Given a clustered data set with no variation within a cluster, shouldn't a regression weighted with the inverse cluster size give the same results as a regression with only one observation per cluster?...
- 170
1
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0
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58
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Clustering or factor analysis for dimensionality reduction in multivariate linear regression
I have dataset describing aggregated purchases from multiple brands. It contains variables:
Brand (ordinal)
Promotion (ordinal)
Sales (numeric)
I need to use linear regression to describe the effect ...
1
vote
0
answers
36
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Regression with unlabeled data from several clusters
I want to characterize the relation of a few input parameters to a single output parameter. The problem I have is that my data is collected from several groups. The groups are defined both by the ...
- 205
2
votes
1
answer
445
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Latent Class Analysis - Interpretation and integration with survival analysis?
I am approaching to Latent Class Analysis to identify "classes" of patients based on some variables.
Question 1: diagnostics of the results. I already gone through the discussion on whether ...
- 706
1
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0
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19
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References about clustered linear regression
I have to write a project about clustered linear regression.
The only resource I have been able to find is https://doi.org/10.1016/S0950-7051(01)00154-X
Any other articles/books that you can point me ...
- 11
3
votes
2
answers
764
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Is 'High School', 'Graduate', 'Unknown' ordinal or nominal data?
My goal is to Feature Engineering the column Education_Level. This is an obvious ordinal data. However, I am having difficulty to put Education_Level to choose <...
0
votes
0
answers
81
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overlapping clusters in R
I have a bunch of observations that are correlated with each other in two different ways, so I'd like to perform logistic regressions but try to account for the correlations among observations to get ...
- 3
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0
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15
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Robust parameter optimization optimizing profit using clustering, classification or regression?
Imagine an algorithm with a parameter applied to different applications. For each application and parameter I can estimate the performance of the algorithm using simulations and historic data.
...
18
votes
5
answers
3k
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Fitting an Orthogonal Grid to Noisy Points
I have a list of coordinates that are meant to form an orthogonal grid that could be rotated. The grid is not necessarily uniform. The rotation is not typically greater than 10°. The coordinates are ...
- 281
2
votes
1
answer
115
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Different Meanings of "Clusters" in Statistics
Typically, I have always come across the term "cluster" within statistics as reference to "clustering" - that is, for example the "K Means Clustering" algorithm. Recently,...
0
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0
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556
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When we use k-means clustering with Light GBM, comparing with Random Forest
I am developping the prediction model with many parameters.
As I was not satisfied by the performance of Random Forest Regression, I tried to use
k-means clustering to regroup the similar variable and ...
- 3
0
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0
answers
276
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cluster by multiple linear regressions
If I have an X and Y feature, can I cluster by what linear regression two populations fall on?
Consider:
In the pink is one regression. In the yellow is another. I know that these two lobes are ...
- 101
1
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0
answers
50
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Regression With Multiple Groups in a Dataset
I am trying to predict grocery store sales from the number of cars in the parking lot. I have a dataset of around 400 stores, over two years, with a count of the number of cars in the lot at the same ...
- 11
1
vote
0
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122
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How to use DecisionTreeClassifier on a problem involving ranks as features? [closed]
Let's say we have a dataset with these columns:
A | B | C | D | E | F | G
I want to predict [E,F,G] based on [A,B] with following rule: top 5 entries order by (SUM(D)/SUM(C)) desc
Pseudo-SQL query ...
1
vote
1
answer
77
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Guidance with piecewise linear data set
I have data that looks like:
As you can see my linear modeling doesn't really work since the y values increase and then stay constant. I want to separate my data for each group into 2 and then ...
- 131
1
vote
0
answers
37
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How to group cities with similarity in order to perform a regression?
My objective is to understand if the average number of students in the classrooms can lead to better grades in a specific exam to all high school students of the cities in a country.
My country has ...
2
votes
1
answer
419
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linear regression inappropriate when there are multiple underlying groups
In this scenario, one group has a clear linear relationship between x and y. Another group doesn't. However, there is no way to differentiate them in the data. In this case, performing a simple linear ...
- 233
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0
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66
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Customer segmentation variable selection
I am trying to do customer segmentation based on their past purchase pattern on different segments like milk products, frozen products, alcohol, grocery and so on
I also have each customer's ...
- 243
1
vote
0
answers
39
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selecting data based on colinearity
I have two variables that are supposed to correlate with each other across the whole dataset, but as you can see in the scatter plot below, it appears that I have a mix of two sub-samples.
One in ...
- 283
0
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0
answers
50
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Cluster regression
I have a dataset and divided the sample into 6 groups based on 4 binary criteria (e.g. "1" for has a Chief Digital Officer and "0" otherwise).
Now I want to conduct a regression of ...
- 1
1
vote
2
answers
4k
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Logistic regression vs clustering analysis
I am having some trouble understanding the difference between clustering and logistic regression. Can you give me some examples of when and why it would be better to use clustering instead of logistic ...
3
votes
1
answer
1k
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Minimize the sum of squared perpendicular distances while computing PCA
Problem (PCA):
Assume that p = 2 and the the predictors are centered. Show that the sum of squared perpendicular
distances from ($x_{i1}, x_{i2})$, i = 1, 2, . . . , n to the line $a_{2}x_{1}−a_{1}x_{...
2
votes
1
answer
69
views
Linear regression on clustering result
I've got a data about mammal body weight responses to increasing air temperature. I want to know whether there are some mammals that respond to the increasing air temperatures differently. Hence, I ...
2
votes
1
answer
50
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What stastical modeling techniques I can use to estimate the boundary of data points in an unsupervised way
Suppose I have a dataset (see the explanation of the background later) as shown in the plot below, where each dot is a sample. To human eyes, there is an obvious boundary which separates samples above ...
- 225
1
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0
answers
168
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How to manually inflate standard errors to approximate clustered SEs
I'm reading a handout on clustering here
It's not clear to me how to compute $\rho_x$ or $\rho_\epsilon$. What is meant by within-cluster correlation of the regression, or within-cluster error ...
- 1,100
1
vote
0
answers
36
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Clustering coefficients of sum-of-sine regression models
I am trying to cluster different time series, based on coefficients yielded by sinusoidal regression. In my case, I have a number of time series of equal length and I fit a sinusoidal regression with ...
- 11
1
vote
0
answers
36
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Selecting a representative graph [closed]
I have a bunch of graphs that if one looks at them can see that they share a clear trend. My question is how to pick a representative graph? Would it make sense to standardize all curves first and ...
- 123
1
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2
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851
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Question about "curve fitting" using ML without known functional form
I am fairly new to machine learning, so I apologize if this is a bad and/or repeat question. It does seem like questions of this nature have been asked at least for linear relationships. Let's say ...
1
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0
answers
15
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Applying clustering to predicted values
I am using clustering techniques such as hierarchical clustering trees to create an index fund modeled on the S&P500 with the correlation between the returns of individual stocks being used as the ...
- 23
1
vote
0
answers
131
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What type of algorithm should I use to analyse questionnaires answers?
Let's say I have a questionnaire, part of it are multiple-choice answers. The person answering may answer (a), (b) or (c) for the first question, then (a), (b), (c), (d), (e) or (f) for the second ...
- 217
4
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1
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450
views
What algorithm to use for fitting several different lines
I have a unique problem I'm not sure how to approach.
I have some data. The data was generated by a function that's basically $k$ different lines ($k$ may or may not be given).
Example:
However, ...
- 141
1
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0
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52
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Pooled panel regression with group-wise clustering by time
How can I compute t-statistics for the coefficients of the pooled panel regression model below such that I account for group-wise clustering by time?
$$
Y_{it} = \alpha + \beta x_{it} + \epsilon_{it}
...
- 305
3
votes
1
answer
63
views
Boundary estimation using statistical techniques
Do you know a good methodology to estimate the boundary between two sets? Here are the specifics of the problem:
I am studying a recursion defined as
$$ 2(n+q) x_{n+2}= (r(n+q) +s)x_{n+1}+((2-r)(n+q)...
1
vote
1
answer
48
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Distinighsing Between Groups on a Bimodal Varaible
I am working with the diamonds data set from the tidyverse package in R.
library(tidyverse)
View(diamonds)
When I plot a histogram of the price variable with 300 ...
- 207
3
votes
1
answer
1k
views
How can the clustered robust standard errors be smaller than the model based ones?
I ran a GEE model and I used it to check the difference between the empirical standard errors and the model-based one. For almost the variables, the empirical standard error was greater than the OLS ...
- 41
0
votes
1
answer
17
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Identify subsets of points that have different correlation
Apologies for the vague question.
I have a plot similar to the figure below, where I compare the distribution of two variables, i.e. the allele frequency in different datasets.
As you can see most ...
- 113
0
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0
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183
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Classifying data, and then performing linear regression on the classes
Is it valid to perform a classification on a data set, separate the data by class, and then perform a regression on each of the groups? The reason why I ask is that the histogram for my data looks ...
-1
votes
1
answer
110
views
Hierarchical clustering in R
I have a dataset of around 25 observations and most of them being categorical.
I have three questions for this.
1- Do the covariates I pick for hierarchical clustering matter or should I try and ...
- 19
1
vote
1
answer
45
views
Simple question on non-normal covariates
I'm analysing some data for a study that has a normal (cognition) outcome, but the predictor of interest (biomarker) is heavily skewed at the top end. The vast majority of the data is pooled around ...
- 11
2
votes
1
answer
245
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ML Combination of Clustering and Regression [closed]
I recently faced a question that I, strangely, never thought of...
Basically, I am considering a setup in which I want to perform regression on a very rich dataset. The chances to overfit are really ...
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1
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0
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22
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Can I use regression output to feed my clustering algorithm?
I'm working on this example:
e-commerce dataset with purchases made by users as well as minimal demographic data like age and gender. The age field is rarely filled. So I want to use regression to ...
2
votes
1
answer
150
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Splitting range of independent variable to maximize prediction within the subranges
I have a dataset with two independent variables $X,Z \in \mathbb{R}$ and a dependent variable $Y \in \mathbb{R}$.
This dataset has the following characteristics:
given some number $z$ and a "small" $...
- 99
7
votes
1
answer
2k
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How to account for multiple measurements of same person in either two-group comparision or regression?
I am running analysis on clinical data collected from patients which are correlated either by time (longitudinally) or more commonly different measurements of the same person at same time (eg. ...
- 73
1
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0
answers
94
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Predicting categories based on a similarity matrix
I am looking for some help in organising some analyses. I will describe what I am trying to do with a fictional example and then talk about some of the things I've thought about already.
Example
I ...
- 641
1
vote
2
answers
562
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Predict duration of tasks with clustering and regression combined in Python
I am trying to predict the length of time (not a time series!) a work task takes, especially technical changes. The output should be a prediction of the duration the task will take in days. As input I ...
- 31
2
votes
1
answer
2k
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If regression is supervised learning is correlation unsupervised learning?
Regression is often given as a simple example for supervised learning because you have a dependent variable and try to build a model with the independent variables.
Could you say that correlation is ...
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