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Quantifying the performance of Stepwise Regression ran on Monte Carlo generated datasets & comparing them to your method of interest

The source data files and scripts referenced here and from whom lines of code are included here can be found in my GitHub Repository for this collaborative research project exploring the properties of ...
Marlen's user avatar
  • 167
1 vote
0 answers
101 views

How to implement kfold and cv into Hybrid feature selection and evaluate the classification model performance?

I have been working on a Hybrid feature selection combined with hyperopt package for hyperparameter tuning and I am thinking about evaluating the performance of several model classifiers. I looked ...
WDpad159's user avatar
  • 111
1 vote
0 answers
27 views

correlated variables & model performance: optimal trade-off

on the back of this topic (When to remove correlated variables) I feel a follow up is needed, with the focus here being on raw performance and risk of distribution shift. assuming little to medium ...
Asher11's user avatar
  • 169
1 vote
0 answers
26 views

How to balance time/effort with transformations, feature selection, and models efficacy in nlp? [closed]

Edit: Question has been edited for reopening (see comment section for justification) Being to new text analytics, I haven't gotten the hang of navigating a typical workflow given the longer times ...
Josh's user avatar
  • 141
13 votes
1 answer
10k views

Why ML model produces different results despite random_state defined? And how to set global random seed for sklearn

I have been running few ML models on same set of data for a binary classification problem with class proportion of 33:67. I had the same algorithms and same set of hyperparamters during yesterday and ...
The Great's user avatar
  • 2,655
0 votes
2 answers
1k views

How can i test the performance of a model when the test data contains seen and unseen data

To test the performance of my model based on some selected features, i try to use unseen and seen data. However, when choosing the accuracy based on all data, the model is almost overfitting since ...
Born New's user avatar
15 votes
4 answers
4k views

How to compare the performance of feature selection methods?

There are several feature selection / variable selection approaches (see for example Guyon & Elisseeff, 2003; Liu et al., 2010): filter methods (e.g., correlation-based, entropy-based, random ...
hopfk's user avatar
  • 341