# Questions tagged [regression]

For questions related to regression (both linear and non-linear) in the context of machine learning and AI.

48 questions with no upvoted or accepted answers
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97 views

### Is a basic neural network architecture better with small datasets?

I'm currently trying to predict 1 output value with 52 input values. The problem is that I only have around 100 rows of data that I can use. Will I get more accurate results when I use a small ...
16 views

### What is a good model for regression problem with binary features and small data?

I am trying to predict the solution time for riddles in which matchsticks are combined into digits and operators. An example of a matchstick riddle is 4-2=8. The solution for this riddle would be ...
111 views

### When should I create a custom loss function?

I'm using a neural network to solve a multi regression problem because I'm trying to predict continuous values. To be more specific, I'm making a tracking algorithm to track the position of an object, ...
29 views

### Is there a classification task with multiple attribute regression?

I'm trying to look for a task that predicts a discrete label first (classification), and then predicts the multiple continuous attributes of the predicted class. I found some papers about multi-output ...
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### What work has been done with Poisson-style regression via neural networks with exponential activation function?

The first neural net I wrote was a classifier. After that, I learned that neural nets can be used for regression tasks, even quantile regression. It has become clear to me that the usual games with ...
101 views

### Which activation functions should I use for polynomial regression?

I am a beginner in machine learning and neural networks. I have only used neural networks for classification problems. My aim is to modify it so that it can work for polynomial regression as well. In ...
31 views

### Can a neural network whose output is uniformly equal to zero learn its way out of it?

I am performing a regression task on sparse images. The images are a result of a physical process with meaningful parameters (actually, they are a superposition of cone-like shapes), and I am trying ...
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### Boston Housing Current Best Model

I'm currently looking for a standard data-set to test some new regression models I've been developing on, and the "Boston Housing Prices" data-set seemed to stand out, since it's very standard. ...
25 views

### Which algorithm and architecture to use for 1:1 matrix transformation of an 8X8 dimension?

I would like to map the simplest 8X8 matrices, one to one, but am not sure which AI algorithm would give the best performance. I am thinking about the DeepLearning4j, however, I don't know which ...
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### How does the regression layer in the localization network of a spatial transformer work?

I am trying to understand the spatial transformer network mentioned in this paper https://papers.nips.cc/paper/5854-spatial-transformer-networks.pdf. I am clear about the last two stages of the ...
48 views

### Predicting population density from satellite imagery

I have very high resolution images from LANDSAT 8 (5 out of 12 bands), which are of various administrative regions of a country. Each image is of variable dimensions, but generally of the order of [...
20 views

### Optimisation of dependence of efficiency of CNN on training data

I got a large dataset of images (dimensions of 16 x 16, 250k samples) and corresponding spherical coordinates (distributed uniformly in each coordinate). On these, I trained a convolutional regression ...
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### How to perform regression with multiple numeric (positive and negative) inputs and one numeric output?

I have a dataset with different types of numerical values (both negative and positive numerical values) for the inputs (for example, -40, -35, 1, 25, 39, etc., that is, multiple inputs) and single ...
24 views

### Literature on Sequence Regresssion

I have some rated time-sequential data and I would like to test if an ANN can learn a correlation between my measurements and ratings. I suspect I could just try a CNN where 1 Dimension is time or an ...
24 views

### why my regression model predict every datapoint to the same value

I am trying to train a SVR but I found that with some combination of features, the trained SVR predict every point in test set to the same value. this problem occurs much more when I use linear kernel ...
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### Can transformers be used to improve regression?

I was recently reading a bit about transformers and I don't understand them very much but I was wondering if anyone knows if any of their techniques such as attention mechanism or anything has been ...
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### Converting inputs as a batch for time series classification would increase accuracy?

I have sensor dataset. I have already classified these data with LSTMs.I have a dataframe with 2 features and a class column. Assume that I take every two rows(inputs) respectively and make the ...
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### Is it possible to use RGB image with decimal values when feeding training data to CNN?

I am working with four grayscale images of float32 data type to perform regression using Keras. Three images are stacked using np.dstack to form a RGB data-set. The ...
27 views

### Predicting the probability of a periodically happening event occurring at a given time

I have encountered this problem on how to predict the probability of a periodically happening event occurring at a given time. For example, we have an event called being_an_undergrad. There are many ...
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### How to use MultiTarget Regression without classes

I would like to forecast a dataset composed of two attributes, a sample is displayed below: ...
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### Multi-target regression using scikit-learn without ytrain

I would like to use the multi-target regression with scikit-learn. However, the examples I've seen use Xtrain and ytrain? What is ytrain in regression? I know y it is used for classes in ...
19 views

### Handling imbalanced data with multiple targets

I have the model which has 3 outputs (it is a regression task, I have the angle of the steering wheel, brake and acceleration). I can divide my values to some smaller bins and in this way I can change ...
22 views

### How should I use deep learning to find the rotation of an object from its 2D image?

I have 6600 images and I am supposed to know the rotation of the object in each image. So, given an image, I want to regress to a single value. My attempt: I use Resnet-18 to extract a feature vector ...
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### What is the best algorithm to solve the regression problem of predicting the number of languages a Wikipedia article can be translated to?

I'm doing a student project where I construct a model predicting the number of languages that a given Wikipedia article is translated into (for example, the article TOYOTA is translated into 93 ...
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### Wind speed forecasting using ARIMA model in Python3

Recently, I started working on time-series models and would mention that I am very new to python and ML as a whole. I tried to implement a time-series model on wind speed data. Being a newbie, I ...
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### Noise reduction in output from regression network

I am building a regression network to predict gravity strength based on meteorological data. I'm getting a fairly good fit, but quite a bit of noise in my output. I can find a lot of info on how to ...
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### What ML algorithm should I use that suits this data?

What if I have some data, let's say I'm trying to answer if education level and IQ affect earnings, and I want to analyze this data and put in a regression model to predict earnings based on the IQ ...
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### Problem fitting data using mlpregressor

I'm training a sklearn.neural_network.mlpregressor by a large data of students performance (an excel file with 740 students and 27 columns that are their qualities) and I want to predict their grades. ...
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### GPU-training on Google Cloud Platform slower than CPU-training

I recently trained Kaggles "Advanced Housing Prices"-Competition using Catboost. For training i used a compute-instance on Google Cloud Platform (GCP) (CPU: Xeon Quad-Core, RAM: 15GB, GPU: ...
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### Finding the 'ultimate resolution' of an ANN

I want to use a neural network to predict the refractive index of a solution. My thinking is, instead of immediately training on many samples, I will first find the 'ultimate resolution' of the ...
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### How to figure out loss weight for label-imbalanced regression problems?

In classification, suppose you have 1 image labeled as cancer and 99 labeled as not cancer, you can just divide the loss weight of "not cancer" by 99. Then you can train the model as this ...
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### Non-linear regression with a neural network

I have to perform a regression on three curves as shown in the following plot. Here, accA (y-axis) is the dependent variable, and ...