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Questions tagged [regression]

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

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32 views

How to find the highest quality alloy?

In a robot making company, a robot must be made from a high quality alloy. There are n candidate alloys to be used for this purpose. Each alloy has p attributes and a quality value q. Assessment and ...
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22 views

Keras regression Model : No probabilities for the predicted number

I have been experimenting with the Deeplearning Keras regression model, where the model predicts the house prices based on the image. I have used a linear regression model: ...
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1answer
14 views

Is consecutive multiple transformation of Y variable a valid approach statistically?

I am going to run a regression analysis. But my response variable is highly right-skewed Firstly I used a log(x+1) transformation and it increased the situation dramatically. But there is still right-...
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1answer
22 views

Multicollinearity and impact of individual features

Assume the following scenario: I have four features: $x_1$, $x_2$, $x_3$, and $x_4$ There are non-negligible multi-collinearity among the features. I want to predict $y$ (response variable) with ...
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20 views

How to calculate error in omega having error in cos(omega*x)?

I have an equation $cos(\omega \times x) = c$. How can I calculate uncertainty in $\omega$ knowing (for each $x$) $c$ and uncertainty in $c$?
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2answers
11 views

Predict part of the input for a fixed target

I dispose of a data set composed of 6 features all of them are numeric and a binary target(taking 0 and 1). How should I proceed in order to predict the values of 2 features knowing the target and the ...
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0answers
21 views

Linear Regression on data with bimodal outcome

I have a data set with 3,000 features and continuous dependent variables of time with 18,000 instances. The histogram of the dependent variables show that the they have a bimodal distribution. I am ...
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1answer
20 views

Normalisation results in R^2 score of 0 - Lasso regression

I am running a regression analysis on a 7000 row dataset with a train/test split of 70%/30%. I am using one variable X to predict a variable ...
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1answer
12 views

Classifcation of non-linear regressions based on their shapes

I have a data set of thousands of individual y ~ x relationships that can have varying shapes in their relationships. For example, they can follow an exponential, asymptotic, logistic or hump-shaped (...
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1answer
32 views

How do I use multilevel regression models?

I have crime event data rows: dayofweek1, region1, hour1, crimetype1 dayofweek2, region2, hour2, crimetype2 ... and I want to use them as factors to model crime ...
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1answer
12 views

Balancing data-sets for regression problems

Unbalanced data-sets are a well described problem for classification-problems. However, for regression similar problems can arise. An example is the data-set where target variable has a very ...
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1answer
17 views

Applying Standardization OLS estimator

I have basic understanding of how to perform linear regression with sklearn and statsmodels. There are several questions that I would like to ask regarding Linear Regression (OLS estimator) : Is ...
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3answers
25 views

How to treat column with potentially meaningful NaNs

My data set has a column that indicates the time taken (in days) for members on a site - each with an ID - to sign up for an event. This can range between 1 to 300 days, with about half of the rows ...
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2answers
121 views

Time series forecasting dilemma. Could feature engineering overcome time dependency?

I keep reading articles about time series forecasting. They all start from the same assumption: time series forecasting can't be treated as a regression/classification problem. It is time dependent, ...
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1answer
120 views

Regression: What defines Linear and non-linear models or functions

Linear regression is used when there is a linear relationship between the input and output variables. Does this linear relationship mean that there is no power over the variables or the parameters? In ...
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1answer
33 views

Scikit model is not able to predict sequence correctly

I am trying to create a regression model using scikit-learn for predicting car price. The input data are, car model(trim), kilometers used, past resale price of similar car and age of used car. I am ...
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0answers
19 views

The purpose of kernel smoothing

Kernel smoothing is described as A kernel smoother is a statistical technique to estimate a real valued function as the weighted average of neighboring observed data. The weight is defined by the ...
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0answers
17 views

How to approach mapping families of vectors on a lattice and forecast resulting value

I describe here a model to describe how neighbours influence a node. I wish to implement it to attempt forecasting to values associate nodes; I post here asking for suggestions on mathematical model ...
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0answers
22 views

Does the add_regressor method on Facebook Prophet also work with categorical variables?

I went through the documentation of Facebook Prophet and was able to build a similar model for my time series dataset. The additional regressors I used were numeric. I achieved a reasonable MAPE score....
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0answers
7 views

Why would predicting a percentage bring my test score R2 nearly to zero?

I am trying to predict the Score on an exam from various predictors. The exam have a total # of points (ScoreMaximum) you can have and each exam can have a different ScoreMaximum. When I try to ...
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11 views

Detect positive and negative changes

Having a dataset like this: What model change I use to show positive and negative transitions between the the 5 variables and correlate them? ...
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0answers
18 views

Feature engineering ideas with dates, coordinates and other variables

I'm working on an ETA problem where I'm trying to estimate a time of arrival for a delivery. I have coordinates of pickup/destination, time of pick , infos about the rider, some other variables that ...
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0answers
62 views

Suggestion for handling specific missing data

I have data, that describes distance from given location to nearest object (e.g. school, shop etc). Because of performance reasons I couldn't scrape the data about objects, that are futher away than 2....
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1answer
29 views

Feature engineering - house price prediction (small dataset) [closed]

I am working on the task of predicting real estate prices. My dataset has only 10 variables described below. I'm thinking about feature engineering but nothing comes to mind. Variables: ...
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0answers
4 views

Minimal example: Keras functional API & multi-input/multi-output regression

Problem: I have a regression problem, where I want to predict two or more numerical outcomes $y_i$ based on a number of numerical features $X_i$. The model would look like: $$y_{1,i}, y_{2,i} = \...
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75 views

Regression on list of 2D time-based data

I have data such that: $D=\{(X_1, Y_1, z_1), (X_2, Y_2, z_2), ...,(X_n, Y_n, z_n)\}, n=1000$ Where: $|(X, Y)_k|$ varies in the $[10, 10000]$ range; $x$ are time values; $y$ are values in $T=\{1, 2, ...
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1answer
33 views

What to do after GridSearchCV()?

I happily created my first NN and performed hyperparameter optimization through GridSearchCV. I just don't know what to do next. Do I have to fit it again with the ...
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2answers
26 views
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1answer
32 views

Correcting for one of multiple strong batch effects in a dataset

I am wondering which statistical tools to use when analysing data that have multiple strong batch effects (distributions vary from one batch to another). I would like to correct batch effect when it ...
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1answer
36 views

When using Absolute Error in Gradient Descent, how to calculate the derivative?

What is the derivative of the Loss Function (Absolute Error) with respect to the feature weights that is used to update the weights? Couldn't find anything specific about it anywhere.
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0answers
25 views

How to choose the suitable Neural Network Architecture for Regression Tasks

I'm working on a project where I want to predict the Vehicle Position from the Vehicle Data like speed, acceleration, etc. The data that I have comes also with a timestamp for each sample (I mean that ...
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2answers
45 views

kNN vs Logistic Regression

Good day, I had this question set as optional homework and wanted to ask for some input. Suppose an individual was to take a data set, divide it in half into training and test data sets and then ...
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0answers
8 views

Threshold for overfitted models

It's common knowledge in DS that overfitted models perform well on training data and poorly on test data. But how do you decide if a model is really overfitting? I have nowhere (books, online courses, ...
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1answer
37 views

Getting monthly revenue predictions for outlets

I am often presented with a task of predicting monthly revenues of retail outlets. Say I have a training set of N outlets, each associated with a series of historical monthly revenues (target) and a ...
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0answers
35 views

How to train regression models on imbalance dataset?

I am trying to train a regression model on the imbalance dataset. For example, the input features are vehicle_type, ...
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1answer
18 views

How to find bias for perceptron algorithm?

My question is very basic. I am starting with ML and am working on the perceptron algorithm. I successfully computed the weights for this input data: ...
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5 views

Multi Output Regression Graph

I am doing a multi output regression using Keras/Tensorflow. I basically have a column of inputs and 2 columns of output points on excel file. I want to fit a curve for that points. The code that i am ...
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1answer
19 views

Multi-Output Regression with Keras

I am trying to do a multi output regression using tensorflow. I have got a dataset in Excel which includes a column of input points and 2 columns of output. I coverted all numbers to numpy objects. ...
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0answers
7 views

How can I predict geographical neighborhoods in a city by coords and income

I have a dataset of households in a city with family income and latitude and longitude. I would like predict virtual zones or neighborhoods with boundaries, grouping close families with similar income....
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0answers
19 views

What is the best approach to train a multi-category regression model?

What is the best approach to train a multi-category regression model (using XBoost decision trees ensemble)? What are the ups and downs of each one? For example, if I want to train a model to predict ...
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1answer
22 views

Minimum Possible Test MSE

I have a little confusion. What follows is from Introduction to Statistical Learning (2013) by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani. My understanding of what is going ...
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0answers
7 views

Bayes factor values

I have two samples A and B with continuous values such as results students. I want to calculate the baysian t test to get the Bayes values. I get the Bayes value of 0.16,so does it mean the null ...
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0answers
35 views

Same coefficient in multivariate regression with dummy variables

Hello Data Science community, I have a model with 1 quantitative variable (y) and 2 categorical variables. In order to work with the categorical variables I have created dummy variables (binary) for ...
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0answers
7 views

Quantile Regression is inconsistent (lower quantiles predicting higher values at times)

While using scikit-learn's GradientBoostingRegressor's "quantile" loss, I noticed that when I try different values of q to fit the data at 0.05 (5%) increments, there are instances when predicting a ...
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0answers
29 views

Mathematics behind multivariate regression

I have sought some help and trained a regression model that takes in a single dependent variable Y and gives the three independent variable R, B and G as output. This has been done in attempt to ...
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0answers
11 views

Prediction interval and probability to increase

Let be $y_i$ some observed values of a given time-series. We denote $\hat{y}_i$ the corresponding predicted values. We also assume to have a prediction interval $p_i$ such that $\hat{y}_i \in p_i = [\...
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17 views

Is there a machine learning method to rank customers credibilty (goodness of a customer)?

I am working on a machine learning project that I want to rank each customer and put on a scale smt like one of those https://cdn1.vectorstock.com/i/1000x1000/90/40/credit-score-indicators-with-color-...
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3answers
47 views

Classification vs Regression Model what should I choose?

I am working on a problem like 'customers next month revenue prediction'. Here revenue will be the target variable. Again we actually segment the customers based on there revenue(like if they give ...
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1answer
27 views

Checking if ML model is possible

How can I check if a machine learning model is feasible on a given dataset? What techniques like EDA, correlation etc. can be used to judge if a model is possible i.e. data and predictor variables ...
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1answer
32 views

sklearn: sklearn.linear_model.HuberRegressor vs sklearn.linear_model.ElasticNet

I am experimenting different loss functions for my regression model. I noticed that in the sklearn, there are: sklearn.linear_model.HuberRegressor and sklearn.linear_model.ElasticNet To me, both use ...