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Fix #634: GaussianNB yellow border activation and missing training parameters - #707

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ArsalanAnwer0:fix/634-gnb-ui
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Fix #634: GaussianNB yellow border activation and missing training parameters#707
ArsalanAnwer0 wants to merge 2 commits into
3C-SCSU:mainfrom
ArsalanAnwer0:fix/634-gnb-ui

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@ArsalanAnwer0

@ArsalanAnwer0 ArsalanAnwer0 commented Mar 4, 2026

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Summary

Fixes #634 two UI issues with the Gaussian Naive Bayes model in ArtificialIntelligence.qml:

  1. Inconsistent UI Activation GaussianNB button border was #439566 (greenish) instead of yellow, making it visually inconsistent with Random Forest and Deep Learning.
  2. Missing Training Parameters No parameter section existed for GaussianNB. Added var_smoothing and priors input fields, consistent with how RF and DL parameters are structured.

Changes

ArtificialIntelligence.qml

  • Fixed border.color on GaussianNB button: #439566"yellow"
  • Added gnbVarSmoothing and gnbPriors property definitions (alongside existing RF/DL properties)
  • Added GaussianNB ColumnLayout parameter section — visible only when currentModel === "GaussianNB" with var_smoothing and priors TextFields

Screenshots

Fix 1 Yellow border on GaussianNB activation (consistent with RF and DL)

Random Forest active (for reference):
RF active

GaussianNB active yellow border now showing correctly:
GNB yellow border


Fix 2 Training parameters now visible when GaussianNB is selected in Train mode

GaussianNB in Train mode var_smoothing and priors now appear:
GNB params visible

Random Forest in Train mode (for comparison):
RF params comparison

Deep Learning in Train mode (for comparison):
DL params comparison

Test plan

  • GaussianNB button shows yellow border when selected (matches RF and DL behaviour)
  • GaussianNB text turns yellow when selected (was already correct, preserved)
  • var_smoothing and priors fields appear in the Parameters panel when GaussianNB is selected in Train mode
  • Parameters are hidden when any other model is selected
  • RF and DL parameter sections are unaffected

@Shariq80

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Great work on this PR! You have successfully resolved both the UI inconsistency and the functional gap by adding the missing var_smoothing and priors training parameters for the Gaussian Naive Bayes model. The layout remains clean and matches the structure used for the other AI models. Everything looks correct and fully addresses issue #634.

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A.I.: Gaussian Naive Bayes

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