B2B sales lead quality prediction using XGBoost classifier. Achieves 81.06% ROC AUC and 84.74% recall on 7,420 IT sales leads. Handles class imbalance, high-cardinality categoricals, and missing data through frequency encoding and threshold optimization. Includes statistical analysis, cross-validation, feature importance, and business insights.
python machine-learning scikit-learn jupyter-notebook cross-validation pandas statistical-analysis xgboost classification data-analysis feature-engineering hyperparameter-tuning imbalanced-data model-evaluation gradient-boosting lead-scoring sales-analytics frequency-encoding b2b-sales threshold-optimization
-
Updated
Nov 10, 2025 - Jupyter Notebook