{"id":23330,"name":"LeadScore Insights","purpose":"A post-training analysis tool for machine learning lead-scoring classifiers, focusing on identifying and visualizing class imbalances and providing recommendations for improved model performance. Addresses the limitations of accuracy as a sole metric.","profitable":1,"date_generated":"Tuesday October 2026 00:15","reference":"project-leadscoreinsights-2026","technology_advise":["Python","PostgreSQL","Medium"],"development_time_estimation_mvp_in_hours":120,"grade":6.8,"category":"devtools","view_count":3,"similar_ideas":[{"id":4920,"name":"Lead Scoring Optimizer","grade":6.9,"category":"fintech"},{"id":16170,"name":"Loss Function Insights Platform","grade":7.8,"category":"devtools"},{"id":22634,"name":"PromptScore Auditor","grade":6.5,"category":"devtools"},{"id":4425,"name":"ML Validation Insights","grade":7.5,"category":null},{"id":19351,"name":"ScoreGuard","grade":8.3,"category":"ai"}],"source_headline":"Accuracy Lied to Me: Precision, Recall, ROC AUC and Cross-Validation in ML"}