lifelines-survival-analysis基于 lifelines 库提供生存分析与 Cox 比例风险建模能力,支持残差诊断、参数化回归模型自定义、时滞转化率分析及比例风险假设检验。
Install via ClawdBot CLI:
clawdbot install tangweigang-jpg/lifelines-survival-analysisGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Generated May 20, 2026
Use survival analysis to model customer churn over time, accounting for censored data and varying risk factors. Helps determine expected customer lifetime and identify high-risk segments for proactive retention.
Apply Cox proportional hazards model to predict time to loan default using borrower features. Enables dynamic risk scoring and early warning systems for credit portfolios.
Model conversion events with time lags from initial contact using specialized survival techniques. Optimize campaign timing and budget allocation by understanding conversion delay distributions.
Build parametric survival models with custom hazard functions for insurance claim prediction. Supports actuarial pricing and reserve estimation by modeling claim occurrence over policy duration.
Charge per analysis session or per model built. Ideal for data science teams needing occasional survival analysis without full platform commitment.
License the survival analysis skill as a module within a larger risk management or CRM platform. Generate revenue through per-seat or per-query pricing.
Offer tailored model building and integration services for enterprises with specific hazard modeling needs. Supplement with training and ongoing support.
💬 Integration Tip
Ensure Python 3.12+ and uv package manager are available. Load USE_CASES.md and ANTI_PATTERNS.md before implementing to avoid common pitfalls.
Scored May 20, 2026
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