Is data-driven modelling and machine learning the same thing?
Jan 27, 2021 · I read a lot of publications about data-driven modeling and machine learning. Most of them use the term interchangeably. So, is data-driven modelling and machine learning actually the …
regression - Is it wrong to remove outliers from dependent variable ...
Sep 1, 2021 · In my opinion it all depends, on the aim of modeling. If your main aim is to estimate properly design statistic model, then removing outliers that are not results of error, or differ …
Identifying confounders in multiple linear regression
May 4, 2022 · Data driven methods for identifying confounders are fraught with difficulties. As an example, steps 1 and 2 depend on the power of the associated test, and introduce uncertainty into …
regression - Variable selection strategies - Cross Validated
May 1, 2024 · I am getting the general feeling from reading around that all of the problems that arise from data-driven variable selection (biased coefficients, small SE's/p-values, etc) occur because one …
How to assess if a model is good in multinomial logistic regression ...
Apr 8, 2015 · Also think about it theoretically - do you think your measures are ordinal? Does an interaction term make sense? Depending on the field, many journals (particularly in the social …
Two ways of obtaining Dynamic Mode Decomposition modes - are …
Nov 23, 2018 · However, in the textbook by prof. Kutz Data-driven modeling and scientific computation, this formula is given for the DMD modes: Φ = UrW Φ = U r W and this is also the formulation that …
Is there any reason to prefer the AIC or BIC over the other?
I think it is more appropriate to call this discussion as "feature" selection or "covariate" selection. To me, model selection is much broader involving specification of the distribution of errors, form of link …
forecasting - Best method for short time-series - Cross Validated
Apr 13, 2017 · Whatever assumptions you make - concerning seasonality, stationarity, &c. - a short time series will give you the chance to detect only the most flagrant violations; so assumptions should be …
R: What do I see in partial dependence plots of gbm and RandomForest?
flattening of partial plot in regions with no data is reasonable: As random forest and CART are data driven modeling, I personally like the concept that these models do not extrapolate.
Variable selection for predictive modeling really needed in 2016?
May 29, 2016 · * Update in November 2017 * Nathan Kutz' 2013 book, Data-Driven Modeling & Scientific Computation: Methods for Complex Systems & Big Data is a mathematical and PDE …