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EDA changelog

1.5.4 (2026-05-16)​

Updated the Multivariate Analysis demo

1.5.3 (2026-05-14)​

Fixed hints in the multivariate analysis demo

1.5.2 (2026-04-24)​

Fix the column_list issue in PCA

1.5.1 (2026-03-27)​

Add formula for prediction in multivariate analysis

1.5.0 (2026-03-13)​

Probabilistic Multi-Parameter Optimization (pMPO) - Enhancements

  • Added support for both numeric and categorical desirability columns
  • Introduced automatic parameter tuning for streamlined configuration
  • Added option to run pMPO without sigmoidal correction
  • New ROC curve and confusion matrix visualizations for model evaluation
  • Expanded correctness test coverage

1.4.12 (2026-01-16)​

Implemented

  • Interactive app for training probabilistic multi-parameter optimization (pMPO) models
  • Export pMPO models to MPO desirability profiles

1.4.11 (2025-11-21)​

Implemented

  • Pareto front viewer
  • Pareto optimization app

1.4.10 (2025-11-05)​

Correct MCL worker termination

1.4.9 (2025-11-04)​

Updated ML lib

1.4.8 (2025-10-15)​

Updated tutorials

1.4.7 (2025-10-01)​

Updated utils and js-api

1.4.6 (2025-09-23)​

Improved ANOVA:

  • Updated the F-test description
  • Implemented the tab control for the results

1.4.5 (2025-09-19)​

Dependencies update

1.4.4 (2025-09-17)​

Improved the PCA dialog

1.4.3 (2025-03-28)​

Updated grok tools

1.4.2 (2025-03-28)​

Updated Multivariate Analysis:

  • Implemented the Quadratic PLS regression
  • Improved MVA and PLS UI/UX

1.3.5 (2025-03-07)​

Vector distance functions support for dimensionality reduction on webGPU and without

1.3.4 (2025-02-28)​

MCL: Updated ML library to support large MCL matrices

1.3.3 (2025-02-20)​

  • Updated the MVA demo

1.3.2 (2025-02-03)​

  • Add History support in MCL Dialog

1.3.1 (2025-01-06)​

  • Rework MCL Viewer

1.2.6 (2024-11-05)​

Fixed:

  • Samples naming in Multivariate Analysis

1.2.5 (2024-11-05)​

Fixed:

  • Labels in Multivariate Analysis

1.2.4 (2024-10-31)​

Fixed:

  • Labels and help links in the PLS tools
  • Fixed k-NN imputer description
  • PCA computations

1.2.3 (2024-10-25)​

Fixed:

  • k-NN imputer input form
  • console output

1.2.2 (2024-09-12)​

Updated ANOVA:

  • Add tests & benchmarks
  • Fixed the incorrect feature column type bug

1.2.1 (2024-09-12)​

  • Add tests & benchmarks for missing values imputation using KNN

1.2.0 (2024-09-10)​

  • 1.21.1 release

1.1.35 (2024-08-28)​

  • Add History support and enable gpu by default if available for dim-red

1.1.34 (2024-08-09)​

  • Updated multivariate analysis
  • Reduced bias in the PLS regression and Multivariate Analysis
  • Fixed linear regression fails

1.1.33 (2024-08-14)​

Bump ml version to 6.6.21

1.1.32 (2024-08-13)​

Add XGBoost to predictive modeling tools

1.1.31 (2024-08-06)​

Add MCL layout with force directed graph and atlas

1.1.30 (2024-07-29)​

Add PLS regression to predictive modeling tools

1.1.29 (2024-07-29)​

Add the softmax classifier

1.1.28 (2024-07-23)​

Bump dependencies versions, datagrok-api to 1.20.0

1.1.27 (2024-06-17)​

Add linear regression

1.1.26 (2024-05-27)​

Add inflation factor to MCL

1.1.25 (2024-05-16)​

Fix inconsistent KNN size in webGPU.

1.1.24 (2024-05-09)​

  • Fix GPU description nullish value.

1.1.23 (2024-05-09)​

  • Disable webGPU input in case if none is available.
  • Improvements to GPU device handling

1.1.22 (2024-04-25)​

Add support for webGPU MCL in full (sparse matrix and expansion/normalization operators)

1.1.21 (2024-04-23)​

Add GPU information to clustering algorithms.

1.1.20 (2024-04-16)​

Improve dimensionality reduction dialog.

1.1.19 (2024-04-15)​

  • PLS components computation
  • Update UI for Multivariate Analysis - main feature & demo app

1.1.18 (2024-04-15)​

Fixed webGPU numeric distance with 0 range

1.1.17 (2024-04-14)​

Features​

  • Add webGPU UMAP implementation.
  • Add webGPU Sparse matrix calculation.
  • Add webGPU option for MCL.

1.1.16 (2024-04-05)​

Add webGPU KNN calculation option to UMAP.

1.1.15 (2024-02-27)​

Add support for post processing functions in dimensionality reduction. The method Dimensionality Reduction (see Top Menu > ML > Dimensionality Reduction) now allows to apply post processing functions to the resulting embeddings.

1.1.14 (2024-02-20)​

Fix NW distance function

1.1.13 (2024-02-12)​

Fix PCA & PLS applying to table from local file

1.1.12 (2024-02-12)​

Add MCL clustering. The method is available in Top Menu > ML > Cluster > MCL.

1.1.11 (2023-12-28)​

Add missing values imputation using the KNN method.

1.1.10 (2023-12-28)​

Add option to pass random seed to dimensionality reduction methods. This allows to reproduce results of dimensionality reduction.

1.1.9 (2023-12-22)​

Improvements to multi column dimensionality reduction.

1.1.8 (2023-12-18)​

Removed separate methods of dimensionality reduction and substituted with a single method Dimensionality Reduction (see Top Menu > ML > Dimensionality Reduction) that supports t-SNE and UMAP. The method allows to use multiple columns (like number, string, Molecule, Macromolecule, etc.) as features with different distance functions. The method also allows to cluster resulting embeddings using DBSCAN algorithm and color resulting scatterplot according to clusters.

1.1.7 (2023-12-14)​

Add DBSCAN clustering to Top Menu > ML > Cluster > DBSCAN.

1.1.6 (2023-10-31)​

Methods descriptions are updated.

1.1.5 (2023-10-23)​

Anova top-menu item is improved.

1.1.4 (2023-10-11)​

Add one-way ANOVA (see Top Menu > ML > Analysis of Variances (ANOVA)...)

1.1.3 (2023-08-24)​

  • The method PCA is replaced to Top Menu > ML > Dimensionality Reduction
  • The method UMPA is added (see Top Menu > ML > Dimensionality Reduction)
  • The method t-SNE is added (see Top Menu > ML > Dimensionality Reduction)
  • The method SPE is added (see Top Menu > ML > Dimensionality Reduction)

1.1.2 (2023-07-27)​

  • Move Multivariate Analysis using partial least squares (PLS) regression to Top Menu | ML
  • In PLS and PCA, just numerical columns can be selected as features