newdigital

Overfitting in machine learning can take on many different forms. Most commonly, it happens when an AI model learns too much of the noise in the data, and fails to make any useful generalizations. This leads to dismal performance when we assess the model on data it has not seen before. There are many techniques that have been developed to mitigate overfitting, but such methods can often prove challenging to implement, especially when you are just getting started on your journey. However,

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Forecasting time series of future prices is critical in various financial market scenarios. Most of the methods that currently exist are based on certain autocorrelation in the data. In other words, we exploit the presence of correlation between time steps that exists both in the input data and in the predicted values.
Among the models gaining popularity are those based on the Transformer architecture that use Self-Attention mechanisms for dynamic autocorrelation estimation. Also, we

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In this article, we build upon the previous work in Part 4 of the MetaQuotes Language 5 (MQL5) series where we added real-time updates to the MQL5 Economic Calendar dashboard. Here, our focus is on making the dashboard more interactive by adding buttons that allow us to directly control the currency pair filters, importance levels, and time range filters, all from the panel itself—without needing to change the settings in the code. We will also include a "Cancel" button that clears the selected

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In the previous part, we dded the ability to restore the EA's state after a restart. It does not matter what the reason was - rebooting the terminal, changing the timeframe on the chart with the EA, launching a more recent version of the EA - in all cases, restoring the state allowed the EA not to start working from scratch and not to lose already open positions, but to continue handling them.

However, the size of the opened positions remained the same for each instance of

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In the previous article "Neural Network in Practice: Least Squares", we looked at how, in very simple cases, we can find an equation that best describes the data set we are using. The equation that was formed in this system was very simple, it used only one variable. We've already shown how to do the calculation, so we'll get straight to the point here. This is because the mathematics used to create an equation based on the values available in the database requires significant knowledge of

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