AC
Machine Learning Model Launcher
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Configure ML Pipeline
Dataset
MNIST (Handwritten Digits)
Iris (Flower Species)
Wine Quality
Breast Cancer
Digits (Small)
70,000 images • 10 classes • 28x28 pixels
Data Split Configuration
Training Set
70%
Validation Set
15%
Test Set
15%
⚠️ Splits must sum to 100%
Model Type
Random Forest
Gradient Boosting
Support Vector Machine (SVM)
K-Nearest Neighbors
Decision Tree
Logistic Regression
Naive Bayes
🚀 Train Model
Reset Configuration
Training Progress
📦
Loading Dataset
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⚙️
Preprocessing Data
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🧠
Training Model
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📊
Evaluating Performance
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📈
Generating Visualizations
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Results & Metrics
🎯
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Training Accuracy
✓
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Validation Accuracy
🎓
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Test Accuracy
⏱️
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Training Time
Confusion Matrix
UMAP Projection
Per-Class Accuracy Analysis
Feature Importance