# Questions tagged [regression]

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

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### Understanding Residuals Plots

I have a residuals plot: Definitions: let's call "blue_line" the line that would exist if I were to draw a straight line by fitting to the blue dots (predictions). My expectation is that if ...
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### Points to remember when embarking on an organization-wide turn to AI solutions

In our organization, we are currently in the phase of building up team, skills to automate and implement AI based solutions. So, we are very early in this AI journey. Right now, we are also working on ...
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### (R) can I convert a categorical variable into a numeric equivalent in linear regression to predict a continuous variable?

Specifically, I have an item code as one of the independent variables that can have several hundred possible values results in underfitting when predicting the projected availability of that item. I'd ...
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### Least mean square linear regression with discrete values on y-axis

So, the idea is that I have floating point numbers on x-axis and discrete values (colors) on y-axis. X-axis stands for measured values (temperature) and y-axis stands for predicted values (colors), ...
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### How many features should be there in a dataset to apply any feature selection method?

I am working on a time series, regression problem, where I have 10 features and 180 observations. I would like to understand what the minimum number of features should be in a dataset to use feature ...
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### My Models giving negative scores

I am new to Data Science. I am trying to use following dataset in order to predict prices for some reason my models except for decision tree is giving negative score. Please help me to build this ...
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### What linear model is common practice to use?

I'm trying to develop a regression model. A possibility is to derive more features of course. The final goal is to find the model with the best results on predicting test set. Are there any guidelines/...
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### Determining which model result is better

I am trying to determine which model result is better. Both results are trying to achieve the same objective, the only difference is the exact data that is being used. I used ...
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### Automate detection of overfitting models based on autoML libraries

I'm trying to use machine learning to impute missing data in series using some auto-ML libraries in python (so far : dabl, FLAML, auto-sklearn and AutoKeras). I know the way to detect overfitting in a ...
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### One predictor variable and 3 response variable (categorical and continuous) [closed]

If I have predictor variables which are a mixture of continuous and categorical, and a response variable that is continuous. What approach should I apply? Linear regression, logistic regression or k ...
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### How to reduce RMS error value in regression analysis & predictions - feature engineering, model selection

There's this dataset containing the metadata of Twitch's top 1,000 streamers of 2020. You can have the details here. I am currently participating in a challenge to predict the values for Followers ...
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### Which algorithm works well for forecasting sales prediction and the reason to choose particular algorithm?

I am working on a project 'Rossmann Sales prediction', in which I have to forecast the sales of Rossmann Stores. So it is a supervised ML problem. I applied random forest. But then in interviews ...
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### How to model a arrival process with increasing features?

Suppose a website records all information related to visits including gender, device, time, etc. When a new impression happens we store it and we want to predict when this person will re-visit the ...
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### Predict apartment prices with two sources of prices

I am asking for help with the following problem. There are two subsamples in the dataset - one where the target is real(valid), and the other where it is approximate (I do not know how it differs yet, ...
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### Best Approach for Predicting NFL Betting Outcomes

I play a game every year with my family, where we compete to make picks against the vegas odds for each NFL game. We aren't actually betting any money, but instead we each try to make the most correct ...
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### The effect of the λ in the Ridge regression

Why by increasing value of λ in Ridge estimator the slope of the line is decreasing? How exactly λ affects to the y = kx + b?
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### How to improve regression neural network?

I am new to deep learning and data science and trying to increase my knowledge by working on some hackathons. Currently, the hackathon project I am working on has the task to predict the closing price ...
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### Automatic detection of ML problem type: Regression or Classification

I am trying to design an algorithm that based on training data automatically detects ML problem type: Regression or Classification. There is no need to say that it is impossible to design such an ...
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### RANSAC and R2, why the r2 score is negative?

I was experimenting with curve_fit, RANSAC and stuff trying to learn the basics and there is one thing I don´t understand. Why is R2 score negative here? ...
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### FFNN vs. RNN for Regressing Physical Sensor Timeseries Data

I'm trying to build a network to regress data from one sensor to another. The target sensor is a scalar time series and the feature sensor can be either a scalar or vector time series. Both timeseries ...
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### Simplest NN regression model for artificial 'rectangular' pattern?

Asuming we are looking for a simplest Tensorflow regression model for nonlinear dataset (1,) -> (1,) (a 'rectangular' pattern): This example dataset has 10000 ...
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### What approach should I take if my feature value changes after the initial prediction?

Goal - Predict number of days the finished good would be delayed from a promised date of delivery? Background - It is only 7 weeks before the promised date of delivery that the demand becomes proxy ...
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### Classification for Ordinal labels - what tree-based methds can i use?

I have a label that has a natural ordering e.g. 0,1,2,3 where 0 is the worst activity measure and 3 is the best. For each label given by the model i need to also give the probability that it belongs ...
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### Prediciting multiple target variables - multioutput regression

I am trying to predict how often a new patient will have specific treatments. The target values are 8 different treatments and the independent variables are age, sex, etc. The outcome of my prediction ...