This is the Linux app named benchm-ml whose latest release can be downloaded as benchm-mlsourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named benchm-ml with OnWorks for free.
Follow these instructions in order to run this app:
- 1. Downloaded this application in your PC.
- 2. Enter in our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 3. Upload this application in such filemanager.
- 4. Start the OnWorks Linux online or Windows online emulator or MACOS online emulator from this website.
- 5. From the OnWorks Linux OS you have just started, goto our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 6. Download the application, install it and run it.
SCREENSHOTS:
benchm-ml
DESCRIPTION:
This repository is designed to provide a minimal benchmark framework comparing commonly used machine learning libraries in terms of scalability, speed, and classification accuracy. The focus is on binary classification tasks without missing data, where inputs can be numeric or categorical (after one-hot encoding). It targets large scale settings by varying the number of observations (n) up to millions and the number of features (after expansion) to about a thousand, to stress test different implementations. The benchmarks cover algorithms like logistic regression, random forest, gradient boosting, and deep neural networks, and they compare across toolkits such as scikit-learn, R packages, xgboost, H2O, Spark MLlib, etc. The repository is structured in logical folders (e.g. “1-linear”, “2-rf”, “3-boosting”, “4-DL”) each corresponding to algorithm categories.
Features
- Comparative benchmarks across ML toolkits (scikit-learn, R, H2O, xgboost, Spark MLlib)
- Algorithm coverage: logistic regression, random forests, boosting, deep neural nets
- Scalable testing with large n (e.g. 10K → 10M) and p (~1K)
- Synthetic data generation and real dataset integration (e.g. Higgs)
- Structured folder organization by algorithm type
- Runtime, memory, and accuracy measurement tools to compare implementations
Programming Language
R
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/benchm-ml.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.