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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2
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1answer
24 views

Best way to measure regression accuracy?

I'm asking because classification problems have very concrete metrics like accuracy that are totally transparent to understand. Whereas regression models seem to have a very large number of possible ...
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0answers
8 views

What to predict in a limited transaction dataset?

I have been given a task with a real transaction dataset. The task is to predict something using either logistic regression or simple binary classification. The columns are as follow: Transaction ID ...
1
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1answer
90 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 ...
1
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0answers
46 views

Is the VC dimension of a MLP regressor a valid upper bound on how many points it can exactly fit?

I want to calculate an upper bound on how many training points an MLP regressor can fit with ~0 error. I don't care about the test error, I want to overfit as much as possible the (few) training ...
0
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1answer
56 views

Do I need to tune the hyper-parameters or more data if SVR model performs poorly?

I am using non-linear data to SVR and have tried tuning the hyperparameters and still have a poor model performance. Do I need more data or format the data for more suitable results? I get similar ...
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0answers
33 views

Multi variate Polynomial Regression

I plotted a grpah of predicted vs actual results with the following code: ...
4
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1answer
310 views

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 ...
1
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1answer
62 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 ...
1
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1answer
37 views

How to pass multiple vectors and numeric features as input to the neural network?

I need help in a regression scenario. I have 12 input features. 4 of which are coordinates (each is a vector) in XYZ plane ...
1
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1answer
153 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 ...
2
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0answers
43 views

What is currently the most competitive regression models/algorithms used on the "Boston Housing Prices" dataset?

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 ...
1
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0answers
13 views

What is the best way to train a text-based regressor model?

I want to build a deep learning model that can predict a continuous value (LogP in this case) given text inputs (SMILES notations in this case), the dataset is as illustrated below. SMILES notations ...
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0answers
7 views

Training and sampling for static model in multivariate time series

Let's suppose I have two time series $x_t$ and $y_t$. I also assume there is an underlying static model of the form: $$ y_t=f(x_t) + \epsilon_t $$ As I said I consider the model a static model meaning ...
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2answers
82 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 ...
2
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1answer
110 views

How to get more accuracy of the logistic regression model?

I am working on a Baby Crying Detection model using logistic regression. Out of $581$ audios, $222$ are of a baby crying. Each audio is of $5$ seconds. what I have done is convert each audio into ...
1
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1answer
43 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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1answer
189 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
11 views

Are ranking models considered discriminative?

I'm developing a model that ranks entries based on cosine similarity to a query. Since it doesn't actually define a boundary between x and y I initially believed that such ranking models are not ...
3
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2answers
141 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, ...
0
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0answers
7 views

Feature selection by Simple regression vs finite impulse response (FIR) method (on TIME Series analysis)

We are working on prediction one company production estimation and the main field of works is like stock market prediction(Time series analysis and process data). So I have some comment on using ...
1
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0answers
26 views

Regress values inside the bounding boxes to predict a value in Object Detection

I am currently working on an object detection task. I have a dataset of Grayscale and Depth Images. The annotation format is x1, y1, x2, y2, class, depth. I have calculated this depth (of each object/...
12
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8answers
17k 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 ...
0
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1answer
44 views

Which loss function could I use to solve a regression problem as a classification problem (where we discretize the labels into buckets)?

I am considering a rather typical regression problem, but, for practice, I am trying to implement this as a classification problem. The setup is as follows. I have $\mathbb{R}$-valued labels $y_i \in [...
0
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0answers
20 views

Image regression - estimating sensors from images

I am trying to use images to predict the sensor data of a racing game. Being a bit of a newcomer I have multiple questions. All help/suggestion is appreciated. Dataset The dataset looks something like:...
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0answers
24 views

Regression for a discrete variable

I'm building a model (neural net) that would predict a quality score for images. Ground truth is given by a 4-level discrete variable (0%, 33%, 67%, 100%), and I would like to build a model that would ...
4
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2answers
110 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 ...
-2
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1answer
55 views

Assumptions of a Linear Regression [closed]

I was going through the concept of Linear Regression and ran into the concept of deciding whether a Linear Regression Model is the best fit for your data by 5 assumptions: Linearity Homoscedasticity ...
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0answers
18 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 ...
0
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1answer
42 views

How to explain that a same DNN model have radically different behaviours with each new initialization and training?

I'm trying to predict the continuous values of a variable $y$ using a Fully Connected Neural Network while providing it with data from a $(3300, 13)$ matrix $X$ where $X[i, :]=[0,...,1,...,0,x_{i}]$. ...
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0answers
20 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 ...
4
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2answers
73 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 ...
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0answers
17 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
32 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 ...
0
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1answer
81 views

How to forecast multiple target attributes in Python?

I need to forecast two non-correlated time-series (non-stationary). A sample is presented below: ...
0
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0answers
15 views

How to use MultiTarget Regression without classes

I would like to forecast a dataset composed of two attributes, a sample is displayed below: ...
0
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0answers
30 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 ...
3
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1answer
597 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 ...
0
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0answers
107 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....
3
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1answer
84 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?
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0answers
46 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 ...
3
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2answers
424 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 '...
-1
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1answer
57 views

What model to use to get a robust model to predict next 3 days of sales even for products that have just sold once ever?

PROJECT: I am working on an e-commerce site where digital products can run out so there is need to reorder them 72h before they run out (reordering them sooner is not a problem but having notification ...
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 ...
3
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1answer
48 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 ...
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0answers
38 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 ...
2
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0answers
25 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 ...
7
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3answers
668 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 ...
1
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0answers
32 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 ...
2
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1answer
104 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 ...
3
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4answers
165 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)....