# Questions tagged [rms]

RMS stands for 'root-mean-square' is a measure of the typical size of a varying quantity. It occurs in the n-denominator form of standard deviation (the RMS deviation from the mean)

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### Internal validation of BART using bootstrap resampling

I developed a BART model for binary outcome predictions given two numeric independent variables using the pbart R package (v2.9). The code looks like this (sub-setting for 23 observations, complete ...
0answers
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### BIC and RMSE are Contradict each other for ARIMA Model Selection using R: Do I Err in Theory or in Practice?

I was surprised to see that RMSE and BIC have contradictory trends for the same time-series data. EDITED The procedures in my code are: simulate a 15 AR series of ...
2answers
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### Root-mean-square error when having multiple prediction horizons

I have a basic question about the root-mean-square error (RMSE). I have a prediction using an ARIMA model. I predicted a time series and use a rolling-horizon approach with overlapping or non-...
1answer
50 views

### How to calculate the RMSPE when the data contains zeros?

I made some predictions with my model and measured its performance using the RMSE. I cannot compare the errors between predictions because some time series have different scales. Some in the 1000's ...
0answers
43 views

### Is RMSE a good non-parametric substitute for Pearson's r?

I am examining how well two non-stationary time series, which are supposed to be representing the same thing, match each other. I believe I should, therefore, be specifically looking for a linear ...
1answer
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### Will a model with a low R² value have higher RMS error rates?

I'm testing different models and my general expectation is that models that have a high coefficient of determination should roughly also have a lower error rate (RMSE in that case) than those with a ...
1answer
28 views

### What is the effect of PCA on the Error?

I am fitting an ElasticNet model using an array of values for alpha and l1_ratio. I then plot the result of the negative root mean squared error from cross validation in a heatmap, which gives me the ...
0answers
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### What does it mean for the RMSE to be the same as the mean of the range?

I made some predictions on some time series data. The plots look good, the predictions line up with the original values quite well. But the error values don't make much sense to me. I calculated the ...
0answers
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### Study on Human Behavior: what is a good value of RMSE when a linear regression is performed on a dataset that represents human behavior? [duplicate]

I am completely new to machine learning. I am working on my undergrad thesis that tries to predict how satisfied a person will be in a specific area by using linear regression. Since this study ...
1answer
23 views

### Presentation of a 3x3 categorical interaction for Cox proportional hazards regression using RMS package

I wanted to verify my presentation of a 3x3 interaction of two categorical variables var1 (exposure of interest) and var2 (effect modifier of interest) using the rms...
0answers
154 views

### How big a difference for test/train RMSE is considered as overfit?

I read that when: RMSE of test > RMSE of train => OVER FITTING of the data. RMSE of test < RMSE of train => UNDER FITTING of the data. Is there a actually delta threshold that determine if ...
0answers
217 views

### How to interpret NRMSE (Normalised Root Mean Square Error) without comparing models?

I have fitted some robust mixed effects linear regression models (using robustlmm::rlmer in R). I have calculated the normalised root mean square error (NRMSE) for these models but I want to make sure ...
0answers
25 views

### How is possible to obtain similar RMSEs but very different Bias between two predictor models?

I'm comparing the results of two predictors models, CNN convolutional neural network and WRF weather numerical model, against a ground truth (Merra). WRF-Merra is the weather numerical model vs Merra ...
0answers
22 views

### How to evaluate a regression model with multiple results?

I created a neural network for time series forecasting. My experiments involve comparing the effects the different regularizers have on the model. I used cross-validation and measured my model's ...
0answers
58 views

### (LSTM with R) How Backtested cross validation RMSE can used for the actual LSTM forecasting model

This blog was super helpful to build LSTM code in R https://www.r-bloggers.com/2018/04/time-series-deep-learning-forecasting-sunspots-with-keras-stateful-lstm-in-r/ So, I tried to use RMSE that is ...
0answers
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### Recommendation Model Performance Analysis

Assume I have to recommendation models A and B. I used two evaluation metrics RMSE and F-score. RMSE values of A is lower than B. However when I was evaluating the F-score I noticed the F-score value ...
1answer
106 views

### Aggregating error metrics like RMSE for multiple time series

With metrics like MAE, taking a mean is the last operation in calculating error values. So given a data set of values and forecasts for multiple series for many steps into the future, taking the mean ...
0answers
70 views

### How to explain RMSE to business folks and in a simple and easy way [duplicate]

If a model predicting 'days to payment etc.' has an RMSE of 25 days and MAE of 20 days. How to explain RMSE of 25 days easily to them, just like the MAE of 20 days (which is average prediction error) ...
0answers
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### Is Root Mean Square Error (RMSE) affected by Simpsons's paradox?

I wonder if RMSE will be different in intra- vs. interindividual calculation. For example I have multilevel data: well-beeing measured at several time points (level 1) nested in people (level 2). I ...
0answers
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### What does “RMSE wrt the 1:1 line” mean

I am reading an article where the authors state root-mean-squared error (RMSE) with respect to the 1:1 line But I'm not sure what they mean? RMSE can be calculated as  RMSE = \sqrt{ \frac{1}{N}\...
1answer
351 views

### What is MCRMSE (mean columnwise root mean squared error)?

The MCRMSE evaluation metric was used in the Kaggle Competitions Africa Soil Property Prediction Challenge(6 years ago) and OpenVaccine: COVID-19 mRNA Vaccine Degradation Prediction(On-going) ...
1answer
80 views

### RMSE to accuracy

I have seen multiple questions and answers about this, but I haven't been able to understand, so, I'm gonna try to ask as simple as possible. I have built several models to forecast future value of a ...
1answer
88 views

### How to apply the uniform shrinkage factor to the logistic regression to get the updated coefficients and intecept in R?

Hope to ask a bit about uniform shrinkage factor in updating the coefficients and intercept of prediction model: I have built up a prediction model with "rms" and got the uniform (global) ...
0answers
63 views

### Using RMSE and AIC to compare three separate “final” models (one with double observations)?

I'm looking at three models (linear mixed effect) looking at crime. The first looks at total crime so there are ~96000 observations. In the second model, I look at crime as a function of crime type (...
1answer
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### What is the difference between RMSE and SEP

I would like to understand the difference between Root Mean Squared Error and the Standard Prediction Error. The SEP formula is simillar to the RMSE, but with an aditional term called bias inside the ...
3answers
565 views

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### RMSE normalization. Number of bins

I am using RMSE (Root mean squared error) as a measure of goodness of fit. I am fitting a formula to binned data. The number of bins is not fixed: if there are less than 5 data values in a certain bin,...
0answers
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### How do I interpret RMSE in layman words? [duplicate]

For example, I am predicting a score that can have value from 0 to 100. The RMSE = 10. How ...
1answer
55 views

### How does the RMSE work?

I am basing my understanding of the Root Mean Squared Error on this answer. From what I understand it averages the error between the target and the prediction. The root and square parts are for ...
1answer
112 views

### Positive model bias but negative percent bias; why?

I'm comparing my training data with some predicted values using the Metrics package in R. When running the bias function, R ...
0answers
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### What is the distribution(root mean square gamma distribution)

What is the distribution when you sample from the gamma distribution and take the root mean square? Please tell me how to prove
0answers
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### Curve Fitting Metrics: Mean Percent Difference

I recently discovered my colleague (not a mathematician) was evaluating their experimental regression analyses by reporting the mean percent difference of each estimated output (from their fitted ...
0answers
157 views

### Hypothesis testing for RMSE

I want to compare two distributions of values. While the mean value is approximatively the same in both distributions, the RMSE in both with respect to 1 is quite different. With RMSE I mean \$\sqrt{(�...
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### Why does the RMSE value goes high? [duplicate]

I have been trying to predict the glucose values of patients by using regression algorithms. I used Support Vector Regression (RMSE: 65), Logistic Regression (RMSE: 86), Linear Regression(RMSE: 64) ...
0answers
324 views

### Calculation of Vector RMSE

I have 2 sets of 2-dimensional vectors, one from observations and one produced by a model. I would like to calculate a statistic similar to the RMSE for these. I believe the correct way of doing this ...
0answers
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### Correct application of RMSE and MAE

I have ~ 120 different datasets (different scales, sample size etc) and for each dataset, I predict ONE statistical parameter (doesn't matter what for my question) with different methods. To compare ...
1answer
56 views

### What does it mean when MAE improved while RMSE worsened?

I am comparing two models: One is a black box that I cannot understand, the other is a GLM. How can I describe why the differences are like this? Is the GLM performing worse than the blackbox?
2answers
642 views

### What is the difference between an RMSE and RMSLE (logarithmic error)?

RMSE vs RMSLE Root Mean Squared Error (RMSE) and Root Mean Squared Logarithmic Error (RMSLE) both are the techniques to find out the difference between the values predicted by the machine learning ...
1answer
68 views

### Assessing loss of different parsimony levels (Cox Model)

I have a Cox Proportional Hazard model with 6 covariates to determine OS. I am now trying to simplify this model by taking some of this covariates down. This is intended for a wide audience so I'm ...