Releases: MAIF/shapash
v2.3.0 : ✨ 2 news Additional dataset columns and Identity card
These 2 new features are designed to understand its model just by browsing the Webapp and have all the necessary information
- With additional dataset columns to have other contextual information than the features of the model
- With an Identity card to better see characteristics of a single sample
✨ Features
#422 Feature/webapp visuals
#424 Feature/id card
#425 Feature/additional data
#426 Target and error columns in dataset
⬆️ Upgrade dependencies and stop support for Python 3.7
#418 maximum version for category_encoders and bump version
#414 maximum version for sklearn
#421 Feature/fix sklearn ce dropping Python 3.7
🐛 Bug fixes
#428 Selecting an index via the Index input box for integers on Windows fails
#429 Selecting an invalid index via the Index input box logs an error
#430 Local explaination plot fails on positive/negative contributions display for specific cases
#433 SmartExplainer method init_app fails when no y_pred
#431 Errors are not managed when manipulating filters on the Shapash Webapp
#432, #434 Update python version for docs
v2.2.2: Patch release: fix on category_encoders version
Fix maximum version for category_encoders waiting for change to adapt new version 2.6.x:
#418 maximum version for category_encoders
v2.2.1: Patch release: fixes on Webapp and sklearn version
This patch release fixes several bugs on webapp:
#403 Webapp : when zooming, labels keeps the short format with "..."
#405 Minor bug on Webapp, When filter and zoom on contribution_plot for global population
#406 Webapp: A small bug with groups of variables and selecting a point
#415 Webapp: bug when click on a single sample, it removes the sub-selection of the feature importance
And fix maximum version for sklearn waiting for change to adapt new version 1.2.x:
#414 maximum version for sklearn
v2.2.0 : ✨ 2 news Features: Picking samples and Dataset Filter
These 2 new features are designed to select samples in the Webapp
- With a new tab "Dataset Filter" to filter more easily with the characteristics of the features
- With a graph that represents the "True values vs Predicted values"
✨ Features
#389 Webapp: Improve the top menu for class selection
#388 Create to tab which contains prediction picking graph and connexion with other graph
#387 add responsive titles, subtitles, axis titles and axis labels to each graph
#386 Add explanation button and popup
#385 Adapt the labels of graphs according to their size
#384 Add tab that contains dataset filters
#378 Adding a plot to the webapp and interactivity with other plots
#377 Add of a prediction error distribution graph
v2.1.1 : Clustering of the correlation matrix
✨ Features
New feature #376
Clustering of the correlation matrix in order to visualize correlations between variables easily.
v2.1.0 : Support to Python3.10
v2.0.2 : Pairwise comparison of Consistency
✨ Features
New feature #364
Pairwise comparison of Consistency : How are differences in contributions distributed across features ?
v2.0.1: Patch release: minor fixes
This patch release fix a bug on display webapp classification #357