Artificial Intelligence Stack Exchange
Artificial Intelligence Stack Exchange

Questions tagged [regression]

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

126 questions
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8 answers

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 fit the spiral. How do data scientists fit data of…
Souradeep Nanda
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10
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3 answers

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 Since I want to predict the user availability…
Guest2000
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8
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1 answer

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 and $y$ is considered as the variable that depends…
TomR
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7
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3 answers

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 {[A=1, B=330, C=1358.238902], result=234.244378} and the…
Cryptonaut
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5
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2 answers

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 classification problems are about classifying…
UsualStranger
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4
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1 answer

Which algorithm can I use to minimise the number of wins of 2 weapons that fight each other in a game?

I have a game that involves 2 weapons, which fight against each other. Each weapon has 5 features/statistics, which have certain range. I can simulate the game $N$ times with randomly initialised values for these statitics, in order to collect a…
Aphrodite
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4
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0 answers

Can AlexNet be changed to produce floating-point outputs in the range $[-1, 1]$, and, if not, which model should I use?

I'm developing a game AI, which tries to master racing simulation. I already trained a CNN (AlexNet) on in-game footage of me playing the game and the pressed keys as the target. I had two main issues with this setup: Extracting the current speed…
TheJD
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4
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1 answer

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?
Marina
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4
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2 answers

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 architecture than when I use multiple layers with a…
Yari Nowicki
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4
votes
1 answer

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 (multivariate). The independent variables are, for…
Riz
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3
votes
1 answer

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 once) that $\tanh$ as activation function of last…
Arnaldo Gualberto
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3
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1 answer

Why does my regression-NN completely fail to predict some points?

I would like to train a NN in order to approximate an unknown function $y = f(x_1,x_2)$. I have a lot of measurements $y = [y_1,\dots,y_K]$ (with K that could be in the range of 10-100 thousands) which come out from either a simulation or a…
MttRch
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3
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2 answers

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 -10 < x < 10. Unfortunately my model's predictions become linear outside of the trained dataset. See…
Mr. Demetrius Michael
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3
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1 answer

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 cloud is in the image. However, what is the general…
Mark Neal
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3
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2 answers

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 possibility that my data are so random so that no…
basilisk
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