# Questions tagged [regression]

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

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14k views

### How to classify data which is spiral in shape?

I have been messing around in tensorflow playground. One of the input data sets is a spiral. No matter what input parameters I choose, no matter how wide and deep the neural network I make, I cannot ...
3answers
611 views

### Do I need classification or regression to predict the availability of a user given some features?

While studying data mining methods I have come to understand that there are two main categories: Predictive methods: Classification Regression Descriptive methods: Clustering Association rules ...
3answers
452 views

### Which predictive algorithm can be used to predict a number given other numbers?

I am currently searching for a supervised learning algorithm that can be used to predict the output given a large enough training set. Here's a simple example. Suppose the training dataset is ...
1answer
180 views

### Can supervised learning be recast as reinforcement learning problem?

Let's assume that there is a sequence of pairs $(x_i, y_i), (x_{i+1}, y_{i+1}), \dots$ of observations and corresponding labels. Let's also assume that the $x$ is considered as independent variable ...
2answers
1k views

### Should the prediction of the body temperature given a camera image be modelled as classification or regression?

I am fairly new to deep learning in general and I am currently facing a problem I want to solve using neural networks and I am unsure if it is a classification or regression problem. I am aware that ...
1answer
131 views

### What is the best approach for multivariable and multivariate regression?

I want to build a multivariable and multivariate regression model in Keras (with TensorFlow as backend), that is, a regression model with multiple values as input (multivariable) and output (...
1answer
50 views

### What is the type of problem requiring to rate images on a scale?

I'm new to the topic, but I've used some off the shelf knowledge about computer vision for classifying images. For example, you can easily generate labels that can determine whether or not e.g. a ...
2answers
104 views

### Is there a possibility that there is no relationship between some inputs and outputs?

I'm doing machine learning projects. I took a look at many datasets I worked with, mostly there are already famous datasets that everyone uses. Let's say I decided to make my own dataset. Is there a ...
1answer
59 views

### What is the relationship between degrees of freedom and the size of the training dataset?

I am going through the book Pattern Recognition by Bishop. At one point he says For $M = 9$, the training set error goes to zero, as we might expect because this polynomial contains 10 degrees of ...
1answer
72 views

### How to define machine learning to cover clustering, classification, and regression?

How to define machine learning to cover clustering, classification, and regression? What unites these problems?
1answer
72 views

### Which models accept numerical parameters and produce a numerical output?

I need a model that will take in a few numerical parameters, and give back a numerical answer (Context: predicting a slope based on environmental factors without having to actually take measurements ...
1answer
2k views

### Why is the hyperbolic tangent with MSE better than the sigmoid with cross-entropy?

Usually, in binary classification problems, we use sigmoid as the activation function of the last layer plus the binary cross-entropy as cost function. However, I have already experienced (more than ...
4answers
123 views

### Regression using neural network

I'd like to ask for any kind of assistance regarding the following problem: I was given the following training data: 100 numbers, each one is a parameter, they together define a number X(also given)....
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 ...
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 ...
1answer
101 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, ...
4answers
134 views

### How is regression machine learning?

In regression, in order to minimize an error function, a functional form of hypothesis $h$ must be decided upon, and it must be assumed (as far as I'm concerned) that $f$, the true mapping of instance ...
1answer
180 views

### Finding the optimal combination of inputs which return maximal output

I am currently working on a problem and now got stuck to implement one of it's steps. This is a simple attempt to explain what I am currently facing, which is something that I am aiming to implement ...
3answers
37 views

### Can predictions of a neural network using ReLU activation be non-linear (i.e. follow the pattern) outside of the scope of trained data?

Training on a quadratic function x = np.linspace(-10, 10, num=1000) np.random.shuffle(x) y = x**2 Will predict an expected quadratic curve between ...
1answer
104 views

### Why is no activation function needed for the output layer of a neural network for regression?

I'm a bit confused about the activation function in the output layer of a neural network trained for regression. In most tutorials, the output layer uses "sigmoid" to bring the results back ...
3answers
152 views

### Using sigmoid in LSTM network for multi-step forecasting

I'm trying to develop a multistep forecasting model using LSTM Network. The model takes three times steps as input and predicting two time_steps. both input and output columns are normalised using ...
1answer
43 views

### Have GANs been used to solve regression problems?

I've noticed that in the last 2 years GANs have become really popular. I know that initially they have been proposed for image classification but I was curious if any of you are aware of any papers ...
2answers
295 views

### How to express accuracy of a regression ANN that uses MSE loss function?

I have a regression MLP network with all input values between 0 and 1, and am using MSE for the loss function. The minimum MSE over the validation sample set comes to 0.019. So how to express the '...
1answer
42 views

### Which NN would you choose to estimate a continuous function $f:\mathbb R^2 \rightarrow \mathbb R$?

Suppose we want to estimate a continuous function $f:\mathbb R^2 \rightarrow \mathbb R$ based on a sample using a NN (around 1000 examples). This function is not bounded. Which architecture would you ...
1answer
36 views

### Predicting a day's data

I have a dataset containing timestamp and temperature. For each day, I have 1440 values viz., I have data for every minute of that day(60minutes * 24hrs = 1440). The Dataset looks like this: As an ...
1answer
79 views

### Imposing physical constraints (previous knowledge) in a neural network for regression

I'm trying to train a neural network to do a multiple non-linear regression $y=f(x_i), i=1,2…N$. So far it works good (low MSE), but some predictions $y$ are “non-physical”, for instance for our ...
1answer
18 views

### Should I model a problem with quantised output as classification or regression?

Say I have some data I am trying to learn, and I'm aware that the output is quantised in some way, e.g. I can get only get discrete values (0.1, 0.2, 0.3...0.9) in a finite range. Would you treat ...
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 ...
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 ...
0answers
98 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 ...
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 ...
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. ...
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 ...
0answers
26 views

1answer
43 views

### How can I perform multivariable regression with neural networks?

I want to use a neural network to perform a multivariable regression, where my dataset contains multiple features, but I can't for the life of me figure it out. Every kind of tutorial on the internet ...
0answers
32 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 ...
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 ...
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 ...
1answer
93 views

### When are multiple hidden layers necessary?

I know that my question probably seems like being asked many times, but Ill try to be more speciffic: Limitations to my question: I am NOT asking about convolutional neural networks, so please, try ...
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 ...
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 ...
0answers
49 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 ...
0answers
46 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 ...