Questions tagged [regression]

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

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Interpreting Aaalen Additive Regression and Covariate Over Time Plots

Came across this tutorial for survival analysis in R here: https://rviews.rstudio.com/2017/09/25/survival-analysis-with-r/ I am not sure how to interpret the summary output or graphs related to the ...
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12 views

Modeling the Price Movement- What analysis should be used

I am trying to model the price of a hotel as the check-in date arrives. I have a data set which looks like- For e.g- if I am looking at the booking date of Dec 31st, I would want to analyze the ...
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9 views

Dense Representation of Proportions Data?

My question is about data representation, but let me first provide a brief description of my application. I have a workload and am executing it on several different machines. Each machine has a ...
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14 views

CNN 3D line angles prediction regression - results of training of phi depend on theta

I am a beginner in "deep learning". What I am trying to do, is to predict two angles of a 3D line projected on a 2D image. The toy model is that I create a line going out from the centre of 48x48 ...
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List of Machine Learning Algorithms for analyzing continuous variables? [on hold]

If I had a set of parameters/variables and a set of output values. How could I know which parameters are actually contributing to the cause of the output values? Could I use feature selection methods ...
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1answer
17 views

Modeling strategy for predicting a day/hour based on my dataset

This is my first time posting here. I'm usually on SO. So I'm not sure if these kind of questions fit into DS stackexchange. I genuinely need opinions on this. What data do I have - ...
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1answer
8 views

Appropriate model metric for a truncated response variable?

Here's a straightforward question I can't seem to find a good answer to. Let's say you're using some variables to predict age. I'm assuming a regression model is the right approach. In this case, what ...
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1answer
18 views

Significant drop from validation accuracy to test accuracy

I am more familiar with classification tasks, though I have been working on a regression problem. I was given a large training dataset (>70k samples) and an independently collected test set (~2k). I ...
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1answer
25 views

Regression methods [closed]

I want to understand what regression methods exist and their purpose. I know the least squares method with which you can build a linear and non-linear model and make predictions. The ARMA model is ...
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Time Series Regression and Exponentially weighted mean of lag values-For Advanced Time Series Experts

I need help for a time series regression problem in engineering features. Background: The dataset has weekly data for sales/orders of hundreds of products for last 145 weeks totalling 450000 ...
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9 views

how RBF works when the input is a very large number?

I used RBF for regression problem as below: h(X)=sum{j in M}( exp(X-Xj)^2 )/2sigma But I get error that exp(3190012) can't be evaluated. which is make sense ...
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Feature selection for circular data in time-series

I'm predicting ozone concentration based on meteorological and seasonal variables. In the feature engineering stage I converted the MONTH, DAY_OF_WEEK, DAY_OF_YEAR to its sin and cosine components ...
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Temperature in Farenheit : Interval or ratio data

According to the Level of Measurement classification, there are four types of data: nominal, ordinal, interval and ratio. The temperature in Fahrenheit and Celsius is often classified as interval ...
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Multivariate Multilag Regression with one shot prediction using LSTM

I am working on a multivariate regression task using a LSTM and I am interested in one shot prediction of my target variable (which is the price of a commodity). For example, the first parameter I ...
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1answer
16 views

ensuring that dependent variable decreases monotonically with independent variable

I have one key relationship between a numeric independent variable X and a numeric dependent variable Y, which is like a negative exponential function determined by 2 parameters. There are other ...
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xgboost: Is there a way to perform regression on rates/percentages data?

I have a dependent variable, $Y$, that is made up of rates/percentages data, so each value is between $0$ and $1$. I was attracted to the xgboost library because it allows focusing in on specific ...
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11 views

Gradient Boosting Partial Dependency Plot

I have been trying to generate a partial development plot using gradient boosting. The Plot looks like as below. My question is why the plot shows two or three steps rather than several broken ...
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1answer
24 views

Feature selection before or after applying filter in Time-series forecasting

I'm predicting ozone concentration based on meteorological variables and ozone value of the previous day. I applied savitzky golay filter to get rid of noise in the time-series dataset. My question ...
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42 views

Hotel Booking Analytics: Perform an analysis in order to understand the movement of the price as the day approaches the check-in date

I am working on a hotel booking dataset. I have transactional level booking data, where each row corresponds to a booking. Please refer to below snippet of the data: I am trying to find out the ...
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1answer
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How to include both origin and destination in your features?

I'm trying to predict the price of transportation for trucking freight. Two important features that I think would be of great impact are Origin and Destination. What's the best way to include that in ...
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1answer
31 views

Differences between a Statistician and a Data Analyst in industry

What is the Difference in the job of a Statistician and a Data Analyst In Industry? My take is that although both analyse data, a Statistician deals with the more theoretical aspects of data such as ...
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1answer
19 views

For a regression model, can you transform all your features to linear to make a better prediction?

I was thinking. Would it be a good approach to check your features one by one (assuming you have a manageable amount of them) and see the relationship they have with your target variable, if they ...
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4answers
25 views

How to resample

I have to deal with a small dataset. I thought that I maght take advantage of resamplin methods to enlarge the population and improve the performance of my regression algorithm. I heard about SMOTE, ...
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1answer
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How to interpret fit from regression (decision) tree which has used 0 variables

I have fit a regression tree to my dataset and the output from summary(tree1) is as follows: ...
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24 views

Can i use survival analysis to predict if a person will “die” or not, and then get the survival time if the person does?

I want to determine, given a project, "How long will it take for this project to be successful ?" Therefore, survival analysis seems like a perfect fit in this case (as I do have some projects that ...
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The Difference between One Hot Encoding and LabelEncoder? [duplicate]

I am working on a ML problem to predict house prices and Zip Code is one feature which will be useful. I am also trying to use ...
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1answer
27 views

Using of 100s of Binary features in regression model

I have 100s of columns with binary values [0, 1] plus some extra columns without binary values. I am trying to do regression model but the model performance is very low. For non-binary features, I ...
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1answer
69 views

Poor performance of regression model for imbalanced data

I am trying to train a neural network model to solve a regression problem. The specificity of my dataset is that it has something like an exponential distribution of target values (imbalanced). ...
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13 views

What type of regression to use when modeling the relationship between a continuous variable and a discrete?

I'd like to create a regression model to find the marginal effect between usage (a rate from 0 - 100%) and tap-distance (1,2,3,4...). I'm working to find how a change in tap-distance to a feature will ...
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2answers
48 views

Prediction after one hot encoding

I have a regression model that I want to make prediction based on values that I will get from an end user. In my dataset, I have one categorical variable region ...
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1answer
127 views

Interpretability of RMSE and R squared scores on cross validation

I'm working on a regression problem with 30k rows in my dataset, decided to use XGBoost mainly to avoid processing data for a quick primitive model. And i noticed upon doing cross-validation that ...
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2answers
40 views

How significant the variables like “id”, “region code” etc are in the predictive modelling?

I participated in one of the hackathon. And there the variables were like id, region, gender, age .etc. It was a regression problem. I did scaling on the variables. But I am not sure what to do with ...
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How to Interpret output Coefficients with python sklearn Support Vector Regression?

I'm looking to interpret the output coefficients from my SVR model. For my case, the rbf kernel has the highest in-sample and out-of-sample performance. However, ...
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1answer
36 views

Neural Network cannot learn nonlinear function

I am currently creating a neural network to learn a function of the following form Data that I want to learn x corresponds to x axis and y to y axis(one dependent and one independent variable) I am ...
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1answer
37 views

Which predictive model is appropriate?

I'm completely lost when trying to choose the type of predictive model for my problem. Is it autoregressive model, nonlinear time series, Markov Chain or other? Can someone please give me some advise? ...
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1answer
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Data driven project for a self-catering accommodation business

I want to apologise in advance for my ignorance but I'm hitting my head in a wall here as I'm not sure how to proceed with my project and I've got no experience in that field even though I'm doing a ...
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1answer
19 views

Predicting a numeric variable from many numeric variables, how to choose a proper structure?

I need to estimate the value of a one numeric variable from the values 8 numeric variables y = f(x_1, ..., x_8). I have an historical dataset where I can relate ...
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Extraction of patterns using interrupted time-series analysis

I am developing a movie recommender system on an online platform. In order to evaluate influence of recommendations, I would like to extract patterns such as “recommending increase young users’ ...
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Resources on Non-Linear Programming and Optimization

With respect to the below question. https://math.stackexchange.com/questions/871370/optimizing-independent-variables-to-maximize-dependent-variable/871421#871421 I am currently building a similar ...
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How to optimize MAPE in regression algorithms

I have a regression task where the label is varying from about 0.001 to 1000. One of the feature called group, for example, group A corresponding label from 0-0.1 and group G corresponding label from ...
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Hyperopt Model runs with 0 seconds duration

I use Hyperopt for Random Forest Regression hyperparameter tuning. my parameterspace is : ...
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2answers
74 views

Regression Algorithms in Production

I am interested in predicting if a doctor would prescribe a specific drug and have chosen Logistic Regression as a starting point. I have a few questions: Is feature selection the first step to take ...
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I have tried 5 different types of model but all returns really low training accuracy (~64%) and low testing accuracy (~14%). What should I do?

I am working with a typical regressor problem. There are $6$ features in the dataset that I am concerned with. There are about $800$ data points in my dataset. The features and the predicted values ...
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2answers
31 views

Can we use DecisionTreeClassifier of sklearn for continuous target variable?

I have a continuous target variable named "quality" which ranges from 0 to 10. Also I have 11 input variables in my dataset. When I'm building my model using DecisionTreeClassifier() of sklearn then ...
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1answer
15 views

Derivative of activation function used in gradient descent algorithms

Why is it necessary to calculate the derivative of activation functions while updating model( regression or NN) parameters? Why is the constant gradient of linear functions considered as a ...
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2answers
28 views

Cost function - ideas

I build xgboost model for regression problem. By the default xgboost optimize $(y - y_{pred})^2$, so the RMSE will be the best eval metric to measure performance. But my task is to build the best ...
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20 views

Which ML algorithm for regression to use for axis parallel points?

If most of the data points are parallel to x-axis which machine learning algorithm to use for regression?
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65 views

Fitting as much points as possible on a line

I want to fit a set of points on a 2D plane that looks like the blue points in the following picture. Instead of having a least square fit (the yellow, dotted line), I want a line that looks like the ...
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1answer
52 views

Neural Network for regression with one dependent and one independent variable

I am trying to make a simple neural network with one dependent and one independent variable. Could you maybe give me a tutorial or help me with the implementation of a neural network with one ...
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1answer
12 views

How to create model for selecting a set of categories with a set of attributes?

I have a couple of hundred categories where each of these categories has a specific set of attributes having different values (historical). The problem I need to solve is to select the best set of ...