All Questions
Tagged with clustering regression
95 questions
0
votes
0
answers
31
views
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 ...
0
votes
0
answers
17
views
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 ...
1
vote
1
answer
48
views
Which kind of analysis could be made to associate a set of genes to clinical values?
I have a set of 5 genes that can be mutated or not, so therefore are intended as dichotomous yes/no vars. I want to identify the effect of the mutation of this genes on a continuous response var.
The ...
4
votes
3
answers
351
views
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 ...
2
votes
1
answer
91
views
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
votes
2
answers
4k
views
Can we use cluster analysis in multiple regression
I am quite new to Data Analytics. I was just wondering whether we can use cluster analysis in Multiple Regression. Let me give you a scenario so that it becomes easier to visualize.
I have a dataset ...
0
votes
0
answers
54
views
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?...
1
vote
0
answers
58
views
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
views
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 ...
2
votes
1
answer
445
views
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 ...
1
vote
0
answers
19
views
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 ...
3
votes
2
answers
764
views
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
views
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 ...
0
votes
0
answers
15
views
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.
...
1
vote
2
answers
296
views
How to sort multiple time-series based on "shape"?
Consider the following toy data:
All prices have been normalised using
$${Price_{Norm} = \frac{Price_{current} - Price_{Min}}{Price_{Max} - Price_{Min}}}$$
Item : Prices
Apples : 0.0, 0.4, 0.8, ...
18
votes
5
answers
3k
views
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 ...
2
votes
1
answer
116
views
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
votes
0
answers
557
views
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 ...
0
votes
0
answers
276
views
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 ...
1
vote
0
answers
50
views
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 ...
1
vote
0
answers
122
views
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
views
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 ...
1
vote
0
answers
37
views
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
views
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 ...
2
votes
0
answers
275
views
Inference with Mixture of Linear Regression
I have used an EM algorithm to fit a finite mixture of linear regression to my data, and cluster them into $k$ clusters.
Now that I have my clusters with the estimated parameters $\beta_k$ and $\...
0
votes
0
answers
66
views
Customer segmentation variable selection
I am trying to do customer segmentation based on their past purchase pattern on different segments like milk products, frozen products, alcohol, grocery and so on
I also have each customer's ...
1
vote
2
answers
674
views
Is it a good idea to cluster predictor variables to try an improve classification performance with logistic regression?
I have trained a logistic regression model on on a selection of 10 socio-demographic predictor variables, all of which are categorical, in order to predict customer behavior on an outcome measure. Out ...
1
vote
0
answers
39
views
selecting data based on colinearity
I have two variables that are supposed to correlate with each other across the whole dataset, but as you can see in the scatter plot below, it appears that I have a mix of two sub-samples.
One in ...
0
votes
0
answers
50
views
Cluster regression
I have a dataset and divided the sample into 6 groups based on 4 binary criteria (e.g. "1" for has a Chief Digital Officer and "0" otherwise).
Now I want to conduct a regression of ...
1
vote
2
answers
4k
views
Logistic regression vs clustering analysis
I am having some trouble understanding the difference between clustering and logistic regression. Can you give me some examples of when and why it would be better to use clustering instead of logistic ...
3
votes
1
answer
1k
views
Minimize the sum of squared perpendicular distances while computing PCA
Problem (PCA):
Assume that p = 2 and the the predictors are centered. Show that the sum of squared perpendicular
distances from ($x_{i1}, x_{i2})$, i = 1, 2, . . . , n to the line $a_{2}x_{1}−a_{1}x_{...
2
votes
2
answers
812
views
What are the advantages of segmentation?
Suppose you want to fit a regression model. You have a data set with multiple attributes. What would be the advantages of segmenting the data set and fitting a regression model to each of the segments?...
9
votes
1
answer
196
views
Question on Inference - Catching Cheating Students
In their paper "Catching cheating students", Levitt and Lin propose a simple reduced-form method to identify cheating of students in exams.
The strategy works as follows: For each possible pair of ...
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
views
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 ...
1
vote
0
answers
168
views
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
vote
0
answers
36
views
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 ...
1
vote
0
answers
36
views
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 ...
1
vote
2
answers
851
views
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
vote
0
answers
15
views
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 ...
1
vote
0
answers
131
views
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 ...
2
votes
1
answer
886
views
Why data shuffling has such a dramatic effect in K-Neighbours regression?
I am trying to use the K-Neighbouts for regression and I find to my surprise that not shuffling the training data has a huge effect on the quality of the prediction.
With shuffling. 98% training data:...
4
votes
1
answer
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, ...
1
vote
0
answers
52
views
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?
$$
Y_{it} = \alpha + \beta x_{it} + \epsilon_{it}
...
3
votes
1
answer
63
views
Boundary estimation using statistical techniques
Do you know a good methodology to estimate the boundary between two sets? Here are the specifics of the problem:
I am studying a recursion defined as
$$ 2(n+q) x_{n+2}= (r(n+q) +s)x_{n+1}+((2-r)(n+q)...
1
vote
1
answer
48
views
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 ...
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 ...
0
votes
1
answer
17
views
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 ...
0
votes
1
answer
61
views
How to predict the second most likely categorical feature?
Suppose I have a dataset $X$ that contains both numerical and categorical features. For concreteness let's assume that one of the categorical features is a sample's ...
0
votes
0
answers
183
views
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 ...