Skip to main content

All Questions

-1votes
1answer
145views

Why linear regression doing not so well with respect to walk-forward validation?

I followed from this question1,question2. I have the following task to do: I have time series data. Training by the consecutive 3 days to predict the each 4th day. Each day data represents one CSV ...
S. M.'s user avatar
0votes
0answers
30views

Linear Regression with coefficients coming from LightGBM

I was wondering if anyone has tried to use a LightGBM to estimate the alpha and beta of a linear regression model. I am looking into this because I am seeking an interpretable model. A direct lgbm ...
Phun's user avatar
  • 101
4votes
1answer
566views

Why linear regression doing well in time series data?

I followed from this question. I have the following task to do: I have time series data. Training by the consecutive 3 days to predict the each 4th day. Each day data represents one CSV file which ...
S. M.'s user avatar
0votes
0answers
20views

Should you seasonally decompose TS data before linear regression?

I want to apply the U-MIDAS method which is basically Least Square regression to a cross sectioned time series. Do I need to seasonally decompose my X and Y and should I test for unit root? Some of ...
J_Bake's user avatar
0votes
1answer
47views

What are some Models/Methods to reduce noise using environmental data?

I have a set of pressure datasets from a mechanical device that frequently moves around the country. I also have several sets of environmental data (Altitude, ambient temperature etc.) from those ...
PressureQuery's user avatar
0votes
1answer
33views

Help me identify the type of plot and the relationship between the dependent variables

Question: I am not sure how to describe the sample graph attached. Can you please help me identify the type of plot and how to statistically measure the relationship between the dependent variable (Y-...
Leo82's user avatar
0votes
1answer
60views

using forecast values from a univariate model as Input to linear regression?

I have weekly time series data for the last 2 years with variables "week", "marketing_spend", "web_traffic", and "revenue" ...
sdave's user avatar
0votes
1answer
104views

Day number as a feature in Linear regression

Goal - To train a Linear regression model for climatic studies. Planned features: - Temperatures, Latitude, Longitude, Day Number (1st February = 32) Would it be correct to include day number like ...
Pixel_Bear's user avatar
0votes
0answers
40views

linear regression - at future time points

I have a dataset of customer transactions containing revenue, customer id, region, product category, product id, support team, date of transaction etc. The data ranges from Jan 2017 to Nov 2nd 2022. ...
The Great's user avatar
0votes
2answers
58views

Tensorflow - do I need to learn computer vision before linear (timeseries) regression?

I'm a newbie to tensorflow / keras and I am currently working my way through Deep Learning with Python (2nd edition) by Francois Chollet. I understand the basics of Computer vision and the MNIST ...
TF Newby's user avatar
1vote
0answers
132views

Linear Regression on Time Series

I have a csv file containing values of X and Y variables. i have been asked to use this to build a linear regression model that can predict the current value of the variable 𝑋 based on its previous ...
Mohammad Khan's user avatar
1vote
0answers
796views

How to Incorporate Upward Trend into XGBoost Time Series Forecasting

I'm working with an XGBoost XGBRegressor model right now, attempting to utilize it to predict time-series forecasted data. My dataset is not publicly available, so I will use general terms to describe ...
C Dixon's user avatar
3votes
2answers
824views

Why do we don't write units with MAE or RSME for regression problem ? If I wish to write the units when how do I identify the units for them?

I have referred many research paper but no one is talking about the units of the metrics. Do MAE , RMSE etc have some units ?
Savita Lonare's user avatar
0votes
1answer
185views

Is there a way to forecast a time series multiple linear regression using externally made dummy variables?

This question concerns question 4h of this textbook exercise. It asks to make future predictions based on a chosen TSLM model which involves an endogenously (if i'm using this right) made dummy ...
Cameron's user avatar
1vote
0answers
20views

Linear regresion for multiple time series

I have some data with this shape: ...
Alexandre Dumont's user avatar

153050per page
close