# Watch Data ### Data Completeness Barker's model used for valuation is a supervised machine learning model and therefore is highly dependent on the quality and comprehensiveness of the input data. For example, every watch at auction we collect information on the watch, the auction, valuation estimates, final sale prices, and more. For watches, Barker has built an understanding of the market by collecting a comprehensive dataset consisting of 800 thousand watch sales from 2012 onwards. ### Influences on Watch Valuation Barker has found the features which provide the greatest uplift in predicting the price of a watch. The features used in the machine learning model include: Watch Identification: * Make * Reference No. * Family Watch Characteristics: * Condition * Year Made * Materials * Tropical-Dials Watch Accessories: * Band type * Certification papers * Original Box --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://barker-valuation-services.gitbook.io/barker-price-warranty/watch-price-warranty-for-consignment/watch-data.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.