MARS®多變數回歸分析軟體-統計分析軟體/新永資訊有限公司

MARS®多變數回歸分析軟體

MARS®多變數回歸分析軟體
編號
類別

統計分析軟體
介紹

MARS®(Multivariate Adaptive Regression Splines) 是 CART 的夥伴，專注於開發和部署準確且易於理解的回歸模型。
價格

推文

產品規格
MARS Multivariate Regression Analysis Software
系統需求

MARS Multivariate Regression Analysis Software

The MARS methodology's approach to regression modeling effectively uncovers important data patterns and relationships that are difficult, if not impossible, for other regression methods to reveal. The MARS modeling engine builds its model by piecing together a series of straight lines with each allowed its own slope. This permits the MARS modeling engine to trace out any pattern detected in the data.

High-Quality Regression and Classification
The MARS Model is designed to predict 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. The MARS engine is also capable of producing high quality classification models for a yes/no outcome. The MARS engine performs variable selection, variable transformation, interaction detection, and self-testing, all automatically and at high speed.

High-Performance Results
Areas where the MARS engine 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).

系統需求

Windows System Requirements
OS:
Windows 7 SP 1 or later, Windows 8 or 8.1, Windows 10.
RAM:
2 GB.
Processor:
Intel® Pentium® 4 or AMD Athlon™ Dual Core, with SSE2 technology.
HD:
2 GB (minimum) free space available.
Screen Resolution:
1024 x 768 or higher.

Linux System Requirements
OS (64-Bit Only):
Ubuntu 14.04 or 16.04, CentOS 6.9 or 7.5, RHEL 6.9 or 7.5.
RAM:
2 GB.
Processor:
Intel® Pentium® 4 or AMD Athlon™ Dual Core, with SSE2 technology.
HD:
2 GB (minimum) free space available.

MARS®多變數回歸分析軟體

MARS 方法的回歸建模方法有效地揭示了其他回歸方法難以甚至不可能揭示的重要數據模式和關係。MARS 建模引擎通過將一系列直線拼接在一起來構建模型，每條直線都有自己的斜率。這允許 MARS 建模引擎追踪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計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引擎自動高速執行變量選擇、變量轉換、交互檢測和自檢。

高性能結果
MARS 引擎表現出非常高性能結果的領域包括預測發電公司的電力需求、將客戶滿意度分數與產品的工程規格相關聯，以及地理信息系統 (GIS) 中的存在/不存在建模。

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