Training Configuration
Auto-tune ON
Data Source
MongoDB · PRINCEAI
Collection
NetworkData
Train / Test Split
80% / 20%
Target Column
Result
Models Evaluated
5 classifiers
Min Accuracy
60%
Models in Competition
Random Forest
n_estimators: [8,16,32,128,256]
Decision Tree
criterion: gini, entropy, log_loss
Gradient Boosting
learning_rate, n_estimators: grid search
Logistic Regression
Default params
AdaBoost
learning_rate, n_estimators: grid search
Pipeline Progress
Idle
Data Ingestion
Fetch from MongoDB
● Waiting
Data Validation
Schema & drift check
● Waiting
Data Transformation
KNN imputation + scaling
● Waiting
Model Training
GridSearch across 5 models
● Waiting
S3 Sync
Push artifacts & model to S3
● Waiting
Training Log
--:--:--Ready. Click "Launch Training Pipeline" to begin.