Side by side
IKPLS vs TorchMetrics
Both stand on statistical analysis software. Which one you can start free with, which one lets you read the code, and what each costs once you pay.
Free plan LinuxMacWindows
IKPLS provides PLS algorithms with NumPy and optional JAX implementations, plus scikit-learn integration and accelerated computation. Its preprocessing, weighting, transformation, and differentiation features cover varied modeling workflows.
Visit IKPLS Free plan Linux
TorchMetrics provides a broad, standardized metric toolkit for PyTorch projects, with distributed and batch-aware calculations. Its free Apache 2.0 licensing and Lightning integration suit developers who can manage optional dependencies and version compatibility.
Visit TorchMetricsThe facts
| IKPLS | TorchMetrics | |
|---|---|---|
| Free plan | Yes | Yes |
| Open source | Not published | Not published |
| Runs on | Linux, Mac, Windows | Linux |
| Lowest paid plan | Not published | Free or on request |
| Plans published | None | 1 |
| Maker | Not published | Not published |
| Website | ikpls.readthedocs.io | lightning.ai |
| On statistical analysis software | #52 of 106 | #48 of 106 |
IKPLS: what it does well
- Free package with Apache-2.0 license
- CPU, GPU, and TPU implementations
- Scikit-learn-conformant wrapper
- Fast cross-validation with leakage-aware preprocessing
- Supports weighted models and reconstruction transforms
What to know first
- Requires Python 3.10 through 3.14
- JAX implementations require an optional extra
- Desktop package requires Python installation
TorchMetrics: what it does well
- More than 100 metrics across many domains
- Supports distributed state synchronization
- Accumulates results across batches
- Custom metrics use Metric subclassing
- Works with PyTorch without Lightning
What to know first
- Linux platform listing only
- Plotting requires matplotlib
- Specialized metrics may need extra dependencies
- Supports latest two Lightning major versions
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