Questions tagged [rmse]
The rmse tag has no usage guidance.
22
questions
1
vote
1answer
17 views
Difference in result in every run of Neural network?
I have written a simple neural network (MLP Regressor), to fit simple data frame columns. To have an optimum architecture, I also defined it as a function to see whether it is converging to a pattern. ...
1
vote
3answers
104 views
Determining which model result is better
I am trying to determine which model result is better. Both results are trying to achieve the same objective, the only difference is the exact data that is being used. I used ...
0
votes
1answer
20 views
How to reduce RMS error value in regression analysis & predictions - feature engineering, model selection
There's this dataset containing the metadata of Twitch's top 1,000 streamers of 2020. You can have the details here.
I am currently participating in a challenge to predict the values for Followers ...
0
votes
1answer
14 views
Comparing RMSEs of multiple test sets having different sizes
The data I have is a time series data (stock returns), and I am training a Random Forest Regressor on it. Total observations = 2499
To better evaluate the performance, I have implemented rolling ...
0
votes
1answer
26 views
Feature engineering: The more features I add the better RMSE I get?
I have a model with 7 features, I'm trying to figure out if I can improve the performance of this model by adding additional features. So I'm relying on the RMSE to measure the accuracy of my ...
0
votes
0answers
11 views
Low MAE, RMSE, RMSLE and MAPE, but also a low R^2
I have a dataframe containing the IDs of 2000 questions, a list of scores representing difficulty, and the following features: how often the question was answered, how often the answer has been ...
0
votes
1answer
25 views
Why is linear regression not doing worse with a low weighted attribute?
I've been able to build a few linear regression models that can predict a material strength quite well: minimum RMSE of 17.95 using 11 attributes that I have selected from 159 original attributes. The ...
2
votes
1answer
37 views
What is bad, good and excellent metric score for time series model?
I have created a couple of models for my master project and I used several metrics for evaluation. I used MSE, MAE, MAPE, RMSE not because I really learned about them a lot, because I saw in many ...
0
votes
0answers
12 views
Analysing Time Series Model performance
Tried to forecast the target variable using Holt's Winter Additive model.
Its a univariate dataset with 6409 data points.
I took a subset of 100 points.
Getting best RMSE is 48220. Min value of target ...
2
votes
0answers
125 views
How to add RMSE value on a plot with ggplot [closed]
I added r2 value and the formula of the regression function but I also want RMSE value on my plot, maybe I need to add something but I could not see a proper answer to this question neither here nor ...
1
vote
1answer
129 views
How to interpret the Mean squared error value in a regression model?
I'm working on a simple linear regression model to predict 'Label' based on 'feature'. The two variables seems to be highly correlate corr=0.99. After splitting the data sample for to training and ...
0
votes
1answer
149 views
How many features do I select when doing feature selection for regression algorithms? Is R2 and RMSE good measures of success for overfitting?
Context: I'm currently crafting and comparing machine learning models to predict housing data. I have around 32000 data points, 42 features, and I'm predicting housing price. I'm comparing Random ...
2
votes
2answers
117 views
RMSE is higher for bigger values of target variable - how to decrease
I am solving a problem with machine learning and I have some data with two integer type independent variables and a continuous dependent variable. I am optimising to RMSE. I had fairly large RMSE ...
1
vote
1answer
93 views
How do you identify whether your RMSE score is good or not?
Im building a XGBoost regression model to predict the values in the range of -3 to 3. Im using Root Mean Squared Error to evaluate the model. With hyper-parameter tuning and everything the best scores ...
1
vote
1answer
150 views
SVR - RMSE is much worse after normalizing the data
I'm building a model using a custom kernel SVR that looks into a few of my dataframe's features and checks the proximity/distance between each pair of datapoints. The features are weigthed and the ...
1
vote
1answer
108 views
Which error metric is good for measuring accuracy
I am estimating water depth with satellite data (predicted value) and would like to validate my result using bathymetry lidar data collected on the field and believed to be more accurate (observed ...
0
votes
1answer
34 views
Perform bootstrapping of an ordinary linear regression model, using B=100 bootstrap resamples of my dataset, and getting RMSE
So Im studying machine learning through R, and Im working with the boston data set from the library MASS. I am practicing bootsrapping. I already carried out analysis to determine how ,many distinct ...
0
votes
1answer
76 views
What could be the reason of having a lower RMSE than MAE?
I used some machine learning algorithms in my dataset and I found that my RMSE goes low than the MAE. What are the most common reasons for that type of typical scenario. Since from my understanding ...
1
vote
0answers
234 views
TensorFlow 2: Find MAE, RMSE for validation dataset in time-series LSTM
TensorFlow 2 "Time series forecasting tutorial" (https://www.tensorflow.org/tutorials/structured_data/time_series#recurrent_neural_network) gives an example of a LSTM multi-step prediction model that ...
3
votes
1answer
264 views
Confusion about the MSE ERROR
I created a Random Forest regressor model and calculated my own error. I also want to calculate MAE, MSE and RMSE to compare my results to similar use cases. I am confused by the results as the values ...
2
votes
2answers
1k views
Reason for generally using RMSE instead of MSE in Linear Regression
In linear regression, why we generally use RMSE instead of MSE? The rationale I know is that it's easy to minimize the error in RMSE instead of MSE by Gradient Descent, but I need to know the exact ...
1
vote
2answers
947 views
What is the difference between an RMSE and RMSLE (logarithmic error)? [closed]
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 ...
