Questions tagged [linear-models]
The linear-models tag has no summary.
28 questions
0votes
0answers
16views
What does the Grenander condition imply about the data-generating process of $(y_i, x_i)$?
Consider a correctly specified linear model $$ y_i = x_i^\top \beta + \varepsilon_i,\quad i=1,\dots,n, $$ where the errors $\varepsilon_i$ are independent with zero mean and finite variance. ...
1vote
3answers
71views
What is the impact of low correlation on regression and classification problems, and how does it affect model performance?
I’m building two models (one for a regression problem and the other for a classification task) but I am facing low correlation in the data (lower in the classification problem than in the regression ...
4votes
1answer
52views
Help on data transformation
I have reaction time as a dependent variable and age as an independent variable. I want to do a linear mixed model analysis. My data is not normally distributed. Should I have to transform data? I ...
1vote
1answer
57views
Minimize $\sum_i||Y_i-AX_i||^2$
I have N data vectors $X_i$ and N target vectors $Y_i$ where $i$ indexes the sample. I would like to learn a linear map $A$ between the data and the target i.e find the matrix $A$ that minimize $$\...
0votes
1answer
37views
Can Linear Models infer Product Sum operation of Features to predict Target?
In a dataset of 9 columns: $X_1-X_8, y$. $y = X_1 * X_5 + X_2 * X_6 + X_3 * X_7 + X_4 * X_8$ Can any form of linear model (anything but SVM, NN, Random Forest, XGBoost, etc.) predict $y$?
0votes
1answer
336views
Effect on regression coefficients by multiplying a constant to a feature
I was solving one quiz question on Coursera and I found an interesting question. If you double the value of a given feature (i.e. a specific column of the feature matrix), what happens to the least-...
1vote
1answer
92views
Linear Regression and Logistic Regression
I'm a beginner, and I'm wondering whether a logistic regression in a nut-shell is just normalizing a linear regression? Correct me if I'm wrong, but I came to this conclusion because the predicted ...
0votes
1answer
106views
Linear Model With Highly Correlated Attributes Producing Inconsistent Weights
I know that having correlated attributes violates the linear model assumption of independent attributes, and I'm not interested in creating a more sophisticated model to tease apart the dependent ...
0votes
1answer
54views
What are different ways to determine how an explanatory variable affect a target variable?
I'm trying to determine a quantitative value by which a target variable change (inflation) by changing an indicator variable (interest rate). The industry basically uses linear models such as VAR. Are ...
1vote
1answer
288views
What are the advantages of model drift vs concept drift in online learning?
I have asked this question here but I'm also posting it here to get a better insight: https://stats.stackexchange.com/questions/602282/what-are-the-advantages-of-model-drift-vs-concept-drift-in-online-...
0votes
1answer
131views
Is Linear kernel SVM always better than Logistic regression?
We know that linear kernel SVM may give better results than logistic regression since maximizing the margin usually leads to more stable results/better displacement of the decision boundary. But is ...
-1votes
1answer
50views
How do the intercept and slope calculated in linear regression relate to the output of lm?
I have been looking at how to calculate coefficients by hand and the example produces $Y = 1,383.471380 + 10.62219546 * X$ However the output shown of lm does not show these values anywhere. How do I ...
0votes
0answers
113views
Linear Regression: Won't adding irrelevant features still improve the prediction
Assume we are predicting weight based on height: this is simple linear regression. If we now add gender, this creates multiple linear regression and improves our model, and makes it more capable of ...
0votes
0answers
29views
Is it a good idea to test the robustness of a Neural Network on a linear relation?
Just to give you more context, I'm currently working on a finance project relying on neural network. I'm principally using Neural Network to achieve regression task. So my neural network aims to ...
1vote
1answer
61views
Temperature lag forecasting
I am working on a data science project on an industrial machine. This machine has two heating infrastructures. (fuel and electricity). It uses these two heatings at the same time, and I am trying to ...