L-Normalizer 2.0

L-Normalizer is a streamlined tool for preparing numeric data so it’s consistent, comparable, and ready for analysis or machine learning. It applies standard normalization and scaling techniques—such as L1/L2 vector normalization, max (L∞), min–max, and z‑score—so differences in magnitude don’t skew your results. Use it to clean datasets, stabilize model training, and ensure fair, repeatable comparisons across vectors and features.

Key capabilities:

• Multiple normalization modes: L1, L2, L∞, min–max, and z‑score
• Per-sample or per-feature scaling to fit your workflow
• Sensible handling of missing values (skip, impute, or drop)
• Batch processing for large datasets
• Reusable presets for consistent pipelines
• Before/after summaries to verify impact at a glance

Ideal for:

• Data scientists and ML engineers standardizing features
• Researchers comparing embeddings or vectors
• Students and analysts preparing datasets for modeling

If you share your specific platform, file formats, or workflow, I can tailor this description even more closely to your version of L-Normalizer.

L-Normalizer is developed by beDSP. The most popular version of this product among our users is 1.0. The name of the program executable file is L-Normalizer.exe.