离群值处理器

POST https://api.elysiatools.com/zh/api/tools/data-outlier-processor

{
  "mcpServers": {
    "elysiatools-data-outlier-processor": {
      "name": "data-outlier-processor",
      "description": "高级离群值检测和处理工具，使用多种统计方法识别、删除或替换数值数据中的异常值。完美用于数据清洗、统计分析和机器学习数据准备。\n\n功能特点：\n- 多种检测方法（IQR、Z-score、修正Z-score、孤立森林）\n- 灵活处理策略（删除、替换均值/中位数/众数、封顶）\n- 自动阈值优化\n- 多维离群值检测\n- 可视化离群值统计和报告\n- 批量处理能力\n- 自定义敏感度级别\n- 综合影响分析\n\n常见用途：\n- 数据清洗和预处理\n- 统计分析准备\n- 机器学习数据集清洗\n- 制造业质量控制\n- 金融异常检测\n- 传感器数据验证",
      "baseUrl": "https://api.elysiatools.com/mcp/sse?toolId=data-outlier-processor",
      "command": "",
      "args": [],
      "env": {},
      "isActive": true,
      "type": "sse"
    }
  }
}

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/list"
}

{
  "jsonrpc": "2.0",
  "id": 2,
  "method": "tools/call",
  "params": {
    "name": "data-outlier-processor",
    "arguments": {
  "inputData": "name,age,salary,score,temperature\nAlice,25,50000,85.2,36.5\nBob,32,75000,92.7,38.1\nCharlie,28,60000,78.9,37.2",
  "targetColumns": "age, salary, score\n\n留空则自动检测数值列",
  "detectionMethod": "iqr",
  "threshold": 1.5,
  "handlingStrategy": "remove",
  "replacementMethod": "median",
  "preserveOriginal": false,
  "markOutliers": true,
  "includeStatistics": true,
  "autoThreshold": false,
  "sensitivity": "medium"
}
  }
}