# Questions tagged [linear-regression]

Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.

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### Linear regression shows b_0 negative while it is a positive quantity

In linear regression, x is weight and y is price; none of the x and y can be negative. The linear regression line with b_0=-57.9 shows a negative y for x<=10 approximately. This signifies that more ...
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### Target variable is discrete ranging from 1 to 14, with each value having same proportion in the dataset, ML models fail miserably

I have a dataset of shape (55314,23). The target variable is league_rank. There are exactly 3951 leagues in this dataset, with each club having a ranking from 1 to 14. The variable is discrete, and ...
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### Is it possible to overfit a simple single variable linear regression model?

I searched this question and the answer I got was about a general regression model, rather than a single variable, linear regression model. If you increase the number of variables, you could fit a ...
27 views

### What can I do do address a regression with systematic bias towards the middle?

I’ve created a linear regression but my predicted output is usually too low for true high values and too high for true low values. I’ve tried introducing a pipeline where I use polynomial features, ...
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### Where do I find dataset for rectangular patch antenna?

I am doing a project in my college, and for that I need a dataset containing the length, width , height along with return loss for different frequency of operation of the rectangular patch antenna. ...
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### What should be the default value for missing ordinal variable

I want to rerank items based on shipping timelines. But I get shipping info from upstream service only when it is less than 4 days. We don't show user when the shipping timeline is more than 4 days. I ...
1 vote
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### Gradient vector starts to increase at some point, gradient descent from scratch

I have a simple linear function y = w0 + w1 * x, where w0 and w1 are weights, And I'm trying to implement a gradient descent for it. I wrote the function and tested in on the data(a dataset of two ...
36 views

### using forecast values from a univariate model as Input to linear regression?

I have weekly time series data for the last 2 years with variables "week", "marketing_spend", "web_traffic", and "revenue" ...
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### My linear regression doesn't work when i try to calculate theta1

I want to create my own linear regression. But my formula of the coefficient theta1 doesn't work i have big values : ...
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### Regression with time series data

I want to predict temperature when time (datetime type, hourly data for five months) and humidity is given. Before starting in python, I created a regression model in excel. But instead of predicting ...
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### Testing RANSAC regression model

I am going to build the model (e.g. multiple linear regression) to predict the appartment cost in my city. First I have to find outliers in training data. For this task RANSAC regression algorithm ...
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### Polynomial Regression coefficient extraction after data normalisation for Mini-Batch SGD

I've written python function that uses a stochastic mini-batch algorithm to compute the optimal polynomial coefficients for a given degree $m$, however this involved normalising the data where  x' = ...