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10+ années
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2693
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Silver Ca tBoost Clusters Real EA is built on the CatBoost algorithm with market data clustering techniques. At its core, the model uses a set of technical features based on silver price data and moving averages (MA). As inputs, it takes distances between price and different MAs across multiple timeframes, as well as the distances between the moving averages themselves. This helps the model figure out how far price is stretched away from its average and how strong the current trend
Gold CatBoost Clusters Real EA operates on the CatBoost algorithm using clustering methods. A set of features is fed into the CatBoost model, constructed based on price data and moving averages (MA). These include distances between the price and MAs across different periods, as well as between the MAs themselves, which help capture deviation and trend strength. The features are normalized—by dividing by the price or MA—to make them scale-invariant. Additionally, rolling window
Majors CatBoost Clusters Real EA operates on the CatBoost algorithm using clustering methods. CatBoost is fed a set of features based on price and moving averages (MA) . What exactly: Distances Price - MA (for different periods) MA − MA → show the deviation and strength of the trend Normalization Division by price or MA → makes features scale-independent Window statistics (WINDOWS) Average, std, max, min → reflects volatility and behavior over a period Lags
