{"id":3511,"date":"2023-08-31T11:12:58","date_gmt":"2023-08-31T11:12:58","guid":{"rendered":"https:\/\/neuraldesigner.com\/learning\/orbit-class\/"},"modified":"2025-10-06T10:36:34","modified_gmt":"2025-10-06T08:36:34","slug":"orbit-class","status":"publish","type":"learning","link":"https:\/\/www.neuraldesigner.com\/learning\/examples\/orbit-class\/","title":{"rendered":"Classify asteroid orbits using machine learning"},"content":{"rendered":"

The primary objective is to develop a machine learning model for classifying asteroid orbits.<\/p>\n

This example is solved with the data science and machine learning platform Neural Designer<\/a>.\u00a0To follow it step by step, you can use the free trial<\/a>.<\/section>\n
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Contents<\/h3>\n
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  1. Application type<\/a>.<\/li>\n
  2. Data set<\/a>.<\/li>\n
  3. Neural network<\/a>.<\/li>\n
  4. Training strategy<\/a>.<\/li>\n
  5. Model selection<\/a>.<\/li>\n
  6. Testing analysis<\/a>.<\/li>\n
  7. Model deployment<\/a>.<\/li>\n
  8. Tutorial video<\/a>.<\/li>\n<\/ol>\n<\/section>\n
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    1. Application type<\/h2>\n

    This is a classification<\/a> project since the variable to be predicted is categorical: AMO, APO, ATE.<\/p>\n

    These orbit types refer to asteroid orbits, allowing the model to categorize orbits according to the aforementioned asteroid orbit classes.<\/p>\n<\/section>\n

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    2. Data set<\/h2>\n

    The first step is to prepare the\u00a0dataset<\/a>, which serves as<\/span>\u00a0the source of information for the classification problem.<\/p>\n

    For that, we need to configure the following concepts:<\/p>\n