{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "$id": "https://raw.githubusercontent.com/api-evangelist/zoho/main/json-schema/zoho-create-auto-mlanalysis-config-schema.json",
  "title": "CreateAutoMLAnalysisConfig",
  "x-generated": "2026-10-04",
  "x-method": "derived",
  "x-generator": "derive-json-schema.py",
  "x-source": "openapi/zoho-modeling-apis-api-openapi.yml#/components/schemas/CreateAutoMLAnalysisConfig",
  "type": "object",
  "properties": {
    "name": {
      "type": "string",
      "description": "Name of the analysis template.",
      "maxLength": 60
    },
    "description": {
      "type": "string",
      "description": "Detailed description of the analysis template.",
      "maxLength": 1000
    },
    "trainingTableId": {
      "type": "integer",
      "format": "int64",
      "description": "Unique ID of the training table used to build the analysis model."
    },
    "targetColumn": {
      "type": "string",
      "description": "Name of the target column from the training table that the model will predict."
    },
    "predictionType": {
      "type": "string",
      "description": "Type of prediction to be performed by the model.",
      "enum": [
        "REGRESSION",
        "CLASSIFICATION",
        "CLUSTERING"
      ]
    },
    "features": {
      "type": "array",
      "description": "List of column names from the training table to use as input features.",
      "items": {
        "type": "string",
        "description": "Each value must be a valid column name."
      },
      "minItems": 1,
      "maxItems": 100
    },
    "serverOption": {
      "type": "integer",
      "description": "Specifies the server memory option.",
      "enum": [
        1,
        2,
        3
      ]
    },
    "algorithms": {
      "type": "object",
      "description": "Configuration for algorithms to be used for training.",
      "properties": {
        "decisionTreeRegression": {
          "type": "object",
          "properties": {
            "minimumSampleSplit": {
              "type": "integer"
            },
            "maximumDepth": {
              "type": "integer"
            }
          }
        },
        "randomForestRegression": {
          "type": "object",
          "properties": {
            "minimumSampleSplit": {
              "type": "integer"
            },
            "maximumDepth": {
              "type": "integer"
            },
            "numberOfTrees": {
              "type": "integer"
            }
          }
        },
        "olsRegression": {
          "type": "object",
          "properties": {
            "intercept": {
              "type": "boolean"
            },
            "allowAlternateModel": {
              "type": "boolean"
            }
          }
        },
        "lassoRegression": {
          "type": "object",
          "properties": {
            "tolerance": {
              "type": "number"
            },
            "shrinkage": {
              "type": "integer"
            },
            "maximumIterations": {
              "type": "integer"
            }
          }
        },
        "ridgeRegression": {
          "type": "object",
          "properties": {
            "shrinkage": {
              "type": "integer"
            }
          }
        },
        "svmRegressor": {
          "type": "object",
          "properties": {
            "epsilon": {
              "type": "number"
            },
            "softMargin": {
              "type": "number"
            },
            "tolerance": {
              "type": "number"
            },
            "epochs": {
              "type": "integer"
            }
          }
        },
        "gradientBoostingRegression": {
          "type": "object",
          "properties": {
            "lossFunction": {
              "type": "string",
              "enum": [
                "LEASTSQUARES",
                "QUANTILE",
                "LEASTABSOLUTEDEVIATION",
                "HUBER"
              ]
            },
            "maximumDepth": {
              "type": "integer"
            },
            "maximumNodes": {
              "type": "integer"
            },
            "nodeSize": {
              "type": "integer"
            },
            "numberOfTrees": {
              "type": "integer"
            },
            "shrinkage": {
              "type": "number"
            },
            "subSample": {
              "type": "number"
            }
          }
        },
        "gradientBoostingClassification": {
          "type": "object",
          "properties": {
            "lossFunction": {
              "type": "string",
              "enum": [
                "LEASTSQUARES",
                "QUANTILE",
                "LEASTABSOLUTEDEVIATION",
                "HUBER"
              ]
            },
            "maximumDepth": {
              "type": "integer"
            },
            "maximumNodes": {
              "type": "integer"
            },
            "nodeSize": {
              "type": "integer"
            },
            "numberOfTrees": {
              "type": "integer"
            },
            "shrinkage": {
              "type": "number"
            },
            "subSample": {
              "type": "number"
            }
          }
        },
        "adaptiveBoost": {
          "type": "object",
          "properties": {
            "maximumDepth": {
              "type": "integer"
            },
            "maximumNodes": {
              "type": "integer"
            },
            "nodeSize": {
              "type": "integer"
            },
            "numberOfTrees": {
              "type": "integer"
            }
          }
        },
        "decisionTreeClassification": {
          "type": "object",
          "properties": {
            "minimumSampleSplit": {
              "type": "integer"
            },
            "maximumDepth": {
              "type": "integer"
            }
          }
        },
        "randomForestClassification": {
          "type": "object",
          "properties": {
            "minimumSampleSplit": {
              "type": "integer"
            },
            "maximumDepth": {
              "type": "integer"
            },
            "numberOfTrees": {
              "type": "integer"
            }
          }
        },
        "logisticRegression": {
          "type": "object",
          "properties": {
            "lambda": {
              "type": "number"
            },
            "maximumIterations": {
              "type": "integer"
            },
            "tolerance": {
              "type": "number"
            }
          }
        },
        "linearDiscriminantAnalysis": {
          "type": "object",
          "properties": {
            "tolerance": {
              "type": "number"
            }
          }
        },
        "maxEntropy": {
          "type": "object",
          "properties": {
            "lambda": {
              "type": "number"
            },
            "maximumIterations": {
              "type": "integer"
            },
            "tolerance": {
              "type": "number"
            }
          }
        },
        "kMeansPP": {
          "type": "object",
          "properties": {
            "clustersCount": {
              "type": "integer"
            },
            "kMax": {
              "type": "integer"
            },
            "chIndexBasedOptimalK": {
              "type": "boolean"
            },
            "calculatePerformanceMetrics": {
              "type": "boolean"
            }
          }
        },
        "kModes": {
          "type": "object",
          "properties": {
            "clustersCount": {
              "type": "integer"
            },
            "minimumClusterCount": {
              "type": "integer"
            },
            "maximumClusterCount": {
              "type": "integer"
            },
            "dissimilarityMeasure": {
              "type": "string",
              "enum": [
                "BINARY",
                "GLOBAL_FREQUENCY",
                "RELATIVE_FREQUENCY",
                "JARO_WINKLER",
                "LEVENSHTEIN",
                "JACCARD"
              ]
            }
          }
        },
        "kPrototypes": {
          "type": "object",
          "properties": {
            "clustersCount": {
              "type": "integer"
            },
            "kMax": {
              "type": "integer"
            },
            "chIndexBasedOptimalK": {
              "type": "boolean"
            },
            "gamma": {
              "type": "number"
            }
          }
        },
        "xMeans": {
          "type": "object",
          "properties": {
            "kMax": {
              "type": "integer"
            },
            "maximumIterations": {
              "type": "integer"
            },
            "tolerance": {
              "type": "number"
            }
          }
        },
        "gMeans": {
          "type": "object",
          "properties": {
            "kMax": {
              "type": "integer"
            },
            "maximumIterations": {
              "type": "integer"
            },
            "tolerance": {
              "type": "number"
            }
          }
        }
      }
    }
  },
  "required": [
    "name",
    "trainingTableId",
    "predictionType",
    "features",
    "serverOption",
    "algorithms"
  ]
}