scoring-model

Compute confidence scores for stock recommendations using a proprietary scoring model.

Updated Feb 5, 2024

Search Tags:#investment #data processing #stock analysis #confidence scoring #model computation

Ready to run

npx skills add https://github.com/mailashishrawat/ml --skill scoring-model

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: scoring-model
Source: https://github.com/mailashishrawat/ml/tree/main/code/anthropic/tradingagent/.claude/skills/scoring-model
Command: npx skills add https://github.com/mailashishrawat/ml --skill scoring-model

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires data/config.json, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the computation of confidence scores for stock recommendations, saving time and reducing manual errors in the investment process.

Core Features & Use Cases

Confidence Scoring: Computes confidence scores for stock recommendations using a unified additive-with-saturating-caps model.
Phase C and E Activation: Triggered during Phase C or E of the stock recommendation pipeline or upon user request.
Scalable and Configurable: Handles various stock scenarios and can be adjusted with a manual weight-refit procedure.
Use Case: For example, when the india-stock-recommender agent enters Phase C or E, or when a user asks to explain confidence scores or audit score breakdowns.

Quick Start

Run the scoring-model skill to compute the confidence score for a given stock candidate.

Frequently Asked Questions about scoring-model

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I automate confidence scoring for stock recommendations?▼

This model automates confidence scoring for stock recommendations by processing input evidence and applying proprietary scoring rules to generate a confidence score and detailed breakdown. It uses an additive-with-saturating-caps model.

What is the additive-with-saturating-caps model used for stock analysis?▼

The additive-with-saturating-caps model is a proprietary scoring method used to compute confidence scores for stock recommendations. It processes input evidence to generate both a final confidence score and a detailed breakdown.

Can I adjust the weight configuration for my stock recommendation confidence scores?▼

Yes, you can adjust the confidence scoring model using a manual weight-refit procedure. This allows you to handle various stock scenarios and tailor the scoring rules to your specific investment data.

Do I need configuration files to compute confidence scores for stock recommendations?▼

Yes, computing confidence scores requires access to specific configuration files and input data. The model depends on data/config.json to process evidence and apply the necessary scoring rules.

When should I trigger the confidence scoring model in the stock recommendation pipeline?▼

You should trigger the confidence scoring model during Phase C or Phase E of the india-stock-recommender pipeline, or when a user requests an explanation of confidence scores or an audit of score breakdowns.