ML Benchmark Results

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1	This spreadsheet contains training runtime comparisons of multiple regression models as implemented by this repo https://github.com/Ludecan/ml_benchmark
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3	The sheets contents are:
4	DDR4@3200 16-20-20-38 v0.1.0 reduced datasets	Benchmark results using release v0.1.0 and the mentioned ram configuration. This version used a reduced number of datasets
5	DDR4@2133 16-20-20-38 v0.1.0 reduced datasets	Benchmark results using release v0.1.0 and the mentioned ram configuration. This version used a reduced number of datasets
6	DDR5@6600 32-39-39-76 v0.1.0	Benchmark results using release v0.1.0 and the mentioned ram configuration. Sheets since this one use an extended number of datasets with more rows x columns configurations
7	DDR5@4800 32-39-39-76 v0.1.0	Benchmark results using release v0.1.0 and the mentioned ram configuration.
8	DDR4@3200 16-20-20-38 v0.1.0	Benchmark results using release v0.1.0 and the mentioned ram configuration.
9	DDR4@2133 16-20-20-38 v0.1.0	Benchmark results using release v0.1.0 and the mentioned ram configuration.
10	DDR5@6600 32-39-39-76 v0.2.0	Benchmark results using release v0.2.0 with updated package versions
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12	Speedups	Summary sheet comparing training runtimes for each model and dataset size across the different RAM speeds
13	RMSEs	Summary sheet comparing RMSE achieved by each model for each dataset size. When looking at these, please consider the caveats mentioned in the repo's README.md
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