Questions tagged [regression]

Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.

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10 views

One LSTM for two currencies or two LSTM one for each currency?

Suppose I am building an LSTM model for currency forecasting. Assume that I am working on two rates: USD vs GBP and USD vs EUR. Should I build one LSTM model with input size of two features (GBP and ...
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22 views

RF regressor for probabilites

I am using sklearn multioutput RF regressor to learn statistics in my data. So my target contains several probabilities for the different features, and the sum of all these probabilities is one as ...
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How does the equation “dW = - (2 * (X^T ).dot(Y - Y_hat)) / m” comes in Linear Regression (using Matrix + Gradient Descent)?

I was trying to code the Linear Regression in Python using Matrix Multiplication method using Gradient Descent and followed a code where there was no mention what is the loss but just a code as Per ...
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SelectKBest for regression `f_regression` behaves weird when changing the random_state parameter when splitting

I am working on a regression project using the Audi dataset from Kaggle. I have looked at other notebooks and i saw that people use SelectKbest. I tried using the same thing, but when I was splitting ...
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2answers
32 views

Multiple Regression, Classification and Boundary Poins

I have two gangs which are doing crimes. And i want to classify them. Lets say I'm looking for a regression function: M(x1, x2) = w1x1 + w2x2 + w3 Now I have ...
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Material Science dataset with feature-dependent inputs

I'm dealing with a material science/chemistry dataset where I have a bunch of duplicates inputs formulas corresponding to different values of a specific features like temperature. It looks something ...
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1answer
22 views

Re-training regression model on covid data

I am trying to re-train a regression model (XGB regressor) which was used in the pre-covid times (Feb 2020). The dependent variable for the model is the number of bookings done, and due to covid, the ...
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Variance of prediction doesn't match input data with Keras model

I'm using Keras to do a regression on inputs. I've tried a lot of different models, and a lot of them converge around the same place. My problem is with the distributions of the results. In order to ...
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What can I infer from a linear correlation of regression coefficients?

I am working on a dataset for classification where each observation is a series of values of a certain measurement $Y$ for a fixed range of values of measurement $X$ (i.e. a discrete mapping from $A \...
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36 views

Use Machine Learning/Neural Network + Distance Measurements to Find the Position of Devices (Localization)

I want to find the position of several devices using at least distance measurements. These measurements are done using a radio, and it might be that not all devices are in radio range (no distance ...
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Feature importance of random forests

I have a dataset with 11 features, I noticed that manipulating these features (eg dropping one or some of them) doesn't affect the error scores of training and testing data, so I had to check the ...
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Find the number of homes with 3000 sq ft , 3 number of bedrooms and 40 years of age?

there is a dataset like this area bedroom age price 2600 3 20 550000 3000 4 15 565000 ... Now the questions are find the price of the ...
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Perform Logistic Regression on housing dataset to predict how many houses will have median price of 500k?

I have a housing dataset with price as a target variable. I know how to use Linear Regression to predict the price of the houses. But how should I find out the number of houses having median price of ...
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How can I create a neural network in Keras, which can find the best patient+treatment paires from a medical dataset? [closed]

I have a medical database for training, the inputs are histological and pathological data (mostly 0/1 data of having some conditions), the outputs are the treatments. And there is an effectiveness ...
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How do you choose a kernel for a discontinuous function in Gaussian Process Regression?

I'm doing Gaussian Process Regression and created a series of functions by gluing other functions together on random places. Here's an example: Perhaps this one is to complicated, but all the ...
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How to process categorical variable having lots of unique values in linear regression?

I have House Price dataset and I am using linear regression to predict the house price. while data preprocessing I found a variable called "Location" and it have around 342 unique value. For ...
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15 views

Neural network type question

This web link is to a site that talks about forecasting building electricity, like a time series regression concept. In the article they talk about the NN architecture as: the architecture of this ...
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1answer
28 views

How close is close enough, with regression?

When exploring different techniques in machine learning (neural networks), I like to use binary classification problems as a test-bed, because it's very easy to understand how well the technique is ...
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Designing a network for multiclass regression

I'd like to model a continuous conditional probability distribution for two classes on a given data set. eg the height of men and women from a set of inputs. I can train a regression model (DNN, CNN, ...
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How to decrease $R^2$ value and change it to positive value [closed]

I'm working on a data, and use regression , as you see bellow: from sklearn.svm import SVR regressor = SVR(kernel = 'linear') regressor.fit(trainX,trainY) above ...
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1answer
21 views

Performing anomalie detection on a battery volatge using LSTM-RNN

I am trying to detect anomalies in a battery output voltage for one month. I have the next data frame, as it is shown the data is collected each minute for each day so I have almost 1420 sample per ...
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51 views

Is it valid to add MAPE as a margin to prediction output?

I've trained a KNNRegressor on predicting used car prices. A given car's actual selling price is R289,995. My model predicts R260,911. I want to be able to tell the user My knn model predicts the deal ...
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Ordinal Regression to understand Google Rankings

I've made a dataset of search engine rankings for web pages versus a host of on-page factors (such as the amount of words on the page or the lenth of the tag) and I would like to try and build a ...
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Regression analysis and least square method relation? [closed]

I want to know where Regression analysis is most used at, what's its competitor methods, and how least square method relates to regression analysis.
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ResourceExhaustedError when building Sequential model

i have a big problem when trying to build my model, ...
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1answer
15 views

Sum of squares for matrix valued data over $\mathbb{R}$ and $\mathbb{C}$

Let us assume we have $k \times k$ matrix valued data and assume this is organized (possibly as time series): $$ M_1, M_2, \ldots, M_n $$ Now, assume we are interested in writing down an error ...
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How to determine activation functions for neural network

I am trying to plan a neural network for regression predictions. The final activation layer should be a linear function, but for hidden layers, do the activation functions need to also be all linear ...
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8 views

Treating continuous data as a classification problem by predicting bins or quintiles

I currently have a model that has several numeric Y or predicted variables Sample Data: Y1 Y2 ... YN 2710 0.32 ... 31231 1710 0.52 ... 51231 I am currently using regression (multioutput regression ...
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1answer
26 views

Machine Learning algorithms and Cross Validation, the best practice

I'm new in Machine Learning, and I'm studying the main concepts behind algorithms from the mathematical point of view. I'm also trying to start implementing some algorithms for regression purposes ...
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38 views

Selecting most important features for multilinear regression

I have a set of 25 features. I would like to choose the best features for my model. Originally, I was looking at the correlation of features with respect to response, and only taking those which are ...
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Keras custom metric doesn't work as loss function [closed]

Referencing my previous question here. I've managed to get my angular error metric working with tf.py_function; ...
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19 views

Correlation Study to Determine Weights Of Fields

I have several input fields, and the content for each field can either be correct or incorrect. These fields are then sent to a black-boxed function (which I can’t control), and the output of the ...
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Normal distribution of errors

I'm trying to project lifetime of customers in my company, based on various parameters I've reached a 64% correlation so far, between the valid and prediction data I'm using light GBM regressor I did ...
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1answer
22 views

Hyperparameter tuning with Bayesian-Optimization

I'm using LightGBM for the regression problem and here is my code. ...
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How to explain ANN can predict much larger output values (e.g., y>2.5) when it was only trained with small output values (y>=2.5)

I have trained models with both ANN and XGBoost. I am wondering that whether ANN has the ability to predict much larger output values (e.g., $y>2.5)$ when it was only trained with small output ...
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33 views

Which data science model is best for explainability for prediction problems?

Imagine you have to create a model to explain to stakeholders e.g. to predict price, weight, sales etc.. Which regression models offer the best in terms of explainability and interprability? ... Which ...
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1answer
28 views

Lasso regression not getting better without random features

First of all, I'm new to lasso regression, so sorry if this feels stupid. I'm trying to build a regression model and wanted to use lasso regression for feature selection as I have quite a few features ...
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9 views

Modeling a time series quantity by modeling its constituent time series

I have a time series target, let's say $Y_1$. This quantity depends on two other time-series quantities deterministically, $Y_2 \text{ and } Y_3$. That is, we have some function which takes $Y_2$ and $...
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24 views

VGG16 based model not learning to recognize emotions from videos

My model looks like this ...
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23 views

Time Series Modelling or Simple regression or something else

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 ...
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30 views

How best to convert label classification into regression?

I have a dataset of genes for which I'm trying to predict genes that cause a disease. Originally I was doing this with a multilabel classification. I had 3 groups: I labeled already known disease-...
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Constraining a Deep Neural Network based on a priori knowledge of a real world system

I am new to this field and to StackExchage, so I guess I'll start by saying hello! I am building a deep neural network to model a physical system which takes a set of inputs based on real-world ...
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1answer
30 views

Creating a training dataset from analytical solution

I am currently redesigning an inverse problem on an experimental technique, but I am having doubts about how to create a training dataset. Here is the problem I am trying to solve: I have already ...
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1answer
28 views

Every one knows data-driven modeling, but what is model-driven (or non data-driven) modeling?

There are hundreds of data-driven machine learning models. It is easy to name a few: neural networks, linear regression, SVM, etc etc... but what is model-driven (or non data-driven) modelling and ...
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How to predict multiple set of coordinates for signboards text localisation through neural network

I am creating a signboard translation model from scratch. I have images of signboards where there are multiple texts and I have the corresponding set of coordinates for multiple texts. I want to ...
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multi-observed features [closed]

I am working on a ML model where individual features may have a highly variable number of observed values. The model will predict a continuous variable so I am planning to use a Regressor. More ...
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13 views

How to do feature reduction for a log-linear regression model

I'm building a log-linear regression model and I have 18 different variables in my model. 13 out of 18 variables I'm using are hot-encoded variables for holiday, e.g. showing which holiday it is. I ...
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11 views

Is it ever advantageous to perform regression on integer-typed label?

Right now, my program's type-checking prevents regression analysis from running on integer labels. It assumes ints are for ordinal/ OHE classification. I just ran a test and verified that it is in ...
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1answer
27 views

How to create custom Keras metric using multiple functions with numpy arrays and matrices?

I'm training a model for predicting position and orientation using regression. I want to implement custom metric using last 3 values of model output to calculate and minimize angular error defined by ...
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Any tips on transfer learning for a regression problem using 4D images as input?

I developed a CNN based on EfficientNet in order to predict the weight of piles of some materials in an image (the labels are the weights in kg and the input is RGBD tensors of the object). I have two ...

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