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• MARS是一個先進的計量預測軟件,它包括數據庫、自建模系統、優化系統,適用于材料研究數據和生產數據的管理,多元非線性建模,以及多因子、多目標優化。
  
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• 自動非線性回歸
  MARS建模引擎非常適合那些喜歡與傳統回歸相似的結果，同時捕獲基本非線性和相互作用的用戶。MARS方法的回歸建模方法有效地揭示了重要的數據模式和關系，這些模式和關系即使不是不可能，也很難被其他回歸方法揭示出來。MARS建模引擎通過將一系列直線拼接在一起來構建其模型，每條直線允許自己的斜率。這允許MARS建模引擎跟蹤數據中檢測到的任何模式。
• 高質量的回歸和分類
  MARS模型旨在預測數字結果，例如移動電話客戶的平均每月賬單或購物者預期在網站訪問中花費的金額。MARS引擎還能夠為是/否結果生成高質量的分類模型。MARS引擎自動且高速地執行變量選擇，變量變換，交互檢測和自檢。
• 高績效結果
  MARS發動機表現出非常高性能的領域包括預測發電公司的電力需求，將客戶滿意度評分與產品的工程規范相關聯，以及地理信息系統（GIS）中的存在/不存在建模。
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• MARS software is ideal for users who prefer results in a form similar to traditional regression while capturing essential nonlinearities and interactions. The MARS approach to regression modeling effectively uncovers important data patterns and relationships that are difficult, if not impossible, for other regression methods to reveal. MARS builds its model by piecing together a series of straight lines with each allowed its own slope. This permits MARS to trace out any pattern detected in the data.
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• HIGH-QUALITY PROBABILITY
  The MARS model is designed to predict continuous numeric outcomes such as the average monthly bill of a mobile phone customer or the amount that a shopper is expected to spend in a web site visit. MARS is also capable of producing high quality probability models for a yes/no outcome. MARS performs variable selection, variable transformation, interaction detection, and self-testing, all automatically and at high speed.
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• HIGH-PERFORMANCE RESULTS
  Areas where MARS has exhibited very high-performance results include forecasting electricity demand for power generating companies, relating customer satisfaction scores to the engineering specifications of products, and presence/absence modeling in geographical information systems (GIS).