Questions tagged [collinearity]
The collinearity tag has no usage guidance.
10
questions
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1answer
26 views
Transforming negative correlated non linear variable to linear positive correlated variable
At my office, I am stuck in a weird situation. I am asked to perform a regression algorithm on the data, in which the target variable is continuous having values range between 0.6 to 0.9 with 8 digits ...
0
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1answer
102 views
How to interpret Variance Inflation Factor (VIF) results?
From various books and blog posts, I understood that the Variance Inflation Factor (VIF) is used to calculate collinearity. They say that VIF till 10 is good. But I have a question.
As we can see in ...
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1answer
21 views
Are time series algorithms immune towards collinearity?
I have a time series dataset with 63 features and a univariate dependent variable. This is my first major time series project, so I was wondering if algorithms like ARIMA and LSTM are immune towards ...
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2answers
203 views
Correlation vs Multicollinearity
I have been taught to check correlation matrix before going for any algorithm.
I have a few questions around the same:
Pearson Correlation is for numerical variables only.
What if we have to check ...
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vote
2answers
403 views
Multicollinearity(Variance Inflation Factor). Variables to remove before doing a model
I am doing an exercise of a Machine Learning System module in python that takes a dataset of cars (cylinders, year, consumption....) and asks for a model, being the variable to predict the consumption ...
2
votes
2answers
31 views
Multicolinearity & accurate weights of predictors
Let’s suppose that the stock value of various companies is the target of my models.
I have some “internal” predictors e.g. yearly sales of each company, sum of salaries at each company etc.
I have ...
2
votes
2answers
41 views
How to measure variable contribution to an observation in a non-linear model?
Based on my model, if I decline someone due to their score, it should be able to provide some reasoning as to which variables mainly contributed to the decision to decline.
Typically in Logistic ...
2
votes
1answer
733 views
Collinearity and Outlier Removal
I am playing with a credit fraud detection dataset at Kaggle. An imbalanced dataset with about 0.1% of fraud transaction. The features are 28 PCs out from a PCA exercise done by the data publisher + ...
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0answers
100 views
Detect multicollinearity in real-life, non-normally distributed data
I am currently trying to figure out whether my data (consisting of thousands of rows, some is numerical, and some are categorical, and some are ordinal) has multicollinearities or not.
One thing I ...
1
vote
1answer
789 views
Should highly correlated features be omitted before applying Lasso?
I would greatly appreciate if you could let me know whether I should omit highly correlated features before using Lasso logistic regression (L1) to do feature ...
