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** types. of algorithms.
1. Linear discriminant analysis
2. Regression
3. Naive Bayes
4. Support vector machines
5. Classification and regression trees
6. Random forests
7. Boosting
etc.
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# Overview
Some `cub::Device*` algorithms are/were documented to be run-to-run deterministic, but the implementations no longer fulfill that guarantee. This has been a major pain point for several …
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I managed to get most algorithms running on the Sparse regression example, but not the DRLS algorithm. I guess it should be applicable to sparse regression, but what needs to be done with:
drls = Pro…
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Issue 1: Data Collection
* Title: Improve data collection process
* Description: Currently, the data collection process for customer churn prediction is manual and time-consuming. We need to exp…
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*Issue migrated from trac ticket # 2886*
**component:** Algorithms.DataAnalysis | **priority:** medium
#### 2018-01-30 16:48:06: @LukasCamera created the issue
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> As a first step in determinist…
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It would be great to have tests for different algorithms. It allows regression testing and it helps with familiarization.
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* Novelty of the project
* In terms of the novelty of the approach, similar projects might already exist in the field of machine learning (ML) education or visualization. To enhance its novelty, th…
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### ML-Crate Repository (Proposing new issue)
:red_circle: **Project Title** : IPL Score Prediction
:red_circle: **Aim** : IPL Score Prediction
:red_circle: **Dataset** : https://www.kaggle.com/dat…
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I think as a standard all scripts should be completely independent and reproducible. I.e. people should be able to copy and paste code in their R REPL session without errors. This is currently not the…
eshom updated
2 years ago
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Hi all,
As in the title, is there a practical way to not use any penalty in the linear regression class ?
This is important because it is a common benchmark in regression algorithms.