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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2answers
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 ...
3
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0answers
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 ...
3
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1answer
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, ...
2
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0answers
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 ...
2
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0answers
60 views

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 ...
2
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0answers
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 ...
2
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0answers
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 ...
2
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0answers
30 views

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. ...
2
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0answers
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 ...
2
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0answers
26 views

Choosing neural network output for prediction (regression) of a dynamical system

I’m trying to train a neural network to approximate the output of a dynamical system $dy/dt=f\left(y(t), u(t) \right)$, namely, given $y(0)$ and $u(t_i), i=1,2...N$ I want the network to predict $y(...
2
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0answers
19 views

How to choose the suitable Neural Network Architecture for Regression Tasks

so I'm working on a Project where I want to predict the Vehicle Position from the Vehicle Data like speed, acceleration etc.. now the data that I have comes also with a timestamp for each sample ( I ...
2
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0answers
23 views

Can two neural networks be better instead of one with a categorical feature?

Let's assume, that I have a neural network with few numerical features and one binary categorical feature. The network in this case is used for regression. I wonder if such a neural network can ...
2
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0answers
25 views

Confidence Maps and Non-Linearity

I am currently trying to improve a CNN architecture that was proposed for generating depth images. The architecture was originally proposed for autonomous driving and it looks like following : The ...
2
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0answers
28 views

Can neuro-fuzzy systems be used for supervised learning tasks with tabular data?

Is it possible to use neuro-fuzzy systems for problems where ANNs are currently being used, for instance, when you have tabular data for regression or classification tasks? What kind of advantage can ...
2
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0answers
125 views

What are the possible neural network architecture for linear regression or time series regression?

I started modeling a linear regression problem using dense layers (layers.dense), which works fine. I am really excited, and now I am trying to model a time series linear regression problem using CNN, ...
1
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0answers
33 views

How to restrain a model's outputs to a certain range without affecting its representative capacity?

CONTEXT I am trying to build a regression model that finds the optimal parameters for a given input. The data I am using are point clouds, with N points and ...
1
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0answers
21 views

Neural network architecture with inputs and outputs being an unkown function each

I am trying to set up a neural network architecture that is able to learn the points of one function (blue curves) from the points of an other one (red curves). I think that it could be somehow ...
1
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0answers
28 views

How to find a parameter combination for a black box using AI?

I am working on a project where I encountered a component which takes 96 arguments (all integer values) and outputs 12 float values. I would like to find a useful combination of these 96 values to ...
1
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0answers
13 views

How do you make a regression model from a binary labeled dataset?

Suppose I have a dataset with hand images. Hand completely opened is labeled as 0 and hand completely closed (fist) are labeled as 1. I also have a bunch of unlabeled images of hands which, if ...
1
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0answers
30 views

3d representation of a regression with two independent variables one of them is categorical and another is continuous

I have hopefully a fundamental question of Do I understand things right. (Thank you in advance and sorry for my English which might be not so good) 1-Preambula 1: I know that if we have 2 independent ...
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0answers
51 views

Can SqueezeNet be used for regression?

I want a model that outputs the pixel coordinates of the tip of my forefinger, and whether it's touching something or not. Those would be 3 output neurons: 2 for the X-Y coordinates and 1, with a ...
1
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0answers
47 views

How MSE should be appliead with multi target deep network?

I'm having a problem understanding how the MSE should be used when working with a multidimensional target, e.g 3 dimensiones. (My outputs are continuois values, not categorical) Let us say I have a ...
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0answers
59 views

Which one is better: multivariate regression with basis expansion or neural networks?

Assume we are given a training dataset $D = \{ (x_i, y_i)\}_{i=1}^{N}$. My question is: which is better? A multivariate regression with basis expansion with independent matrix $X$ and dependent ...
1
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1answer
73 views

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 ...
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0answers
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 [...
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0answers
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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0answers
39 views

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 ...
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0answers
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 ...
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0answers
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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0answers
3 views

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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0answers
17 views

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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0answers
15 views

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 ...
0
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0answers
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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0answers
13 views

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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0answers
27 views

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 ...
0
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1answer
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 ...
0
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0answers
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 ...
0
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1answer
51 views

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 ...
0
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1answer
89 views

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 ...
0
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0answers
31 views

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 ...
0
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2answers
64 views

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 ...
0
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0answers
34 views

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. ...
0
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0answers
68 views

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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0answers
59 views

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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0answers
18 views

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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0answers
39 views

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 ...
0
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1answer
93 views

Possible model to use to find pixel locations of objects

I want to make a model that outputs the centre pixel of objects appearing in an image. My current method involves using a CNN with L2 loss to output an image of equivalent size to the input where ...
0
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0answers
105 views

Remove drawbacks of Neural Network regressor as compared Polynomial Regressor

As far as my knowledge goes (might be a bit vague and not mathematical), a Neural Network can and should only be able to approximate a bounded function, which is not the case of a Polynomial Regressor....