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  1. Data label for time series mining(Part 1)

    by , 04-30-2024 at 02:24 PM
    When we design artificial intelligence models, we often need to prepare data first. Good data quality will allow us to get twice the result with half the effort in model training and validation. But our foreign exchange or stock data is special, which contains complex market information and time information, and data labeling is difficult, but we can easily analyze the trend in historical data on the chart.

    This section introduces a method of making data sets with trend marks by EA
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  2. Neural networks made easy (Part 68): Offline Preference-guided Policy Optimization

    by , 04-28-2024 at 03:31 PM
    Reinforcement learning is a universal platform for learning optimal behavior policies in the environment under exploration. Policy optimality is achieved by maximizing the rewards received from the environment during interaction with it. But herein lies one of the main problems of this approach. The creation of an appropriate reward function often requires significant human effort. Additionally, rewards may be sparse and/or insufficient to express the true learning goal. As one of the options
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  3. The Disagreement Problem: Diving Deeper into The Complexity Explainability in AI

    by , 04-25-2024 at 02:05 PM
    The disagreement is an open area of research in an interdisciplinary field known as Explainable Artificial Intelligence (XAI). Explainable Artificial Intelligence attempts to help us understand how our models are arriving at their decisions but unfortunately everything is easier said than done.

    We are all aware that machine learning models and available datasets are growing larger and more complex. As a matter of fact, the data scientists who develop machine learning algorithms cannot
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  4. Neural networks made easy (Part 37): Sparse Attention

    by , 04-20-2024 at 02:24 PM
    In the previous article, we discussed relational models which use attention mechanisms in their architecture. We used this model to create an Expert Advisor, and the resulting EA showed good results. However, we noticed that the model's learning rate was lower compared to our earlier experiments. This is due to the fact that the transformer block used in the model is a rather complex architectural solution performing a large number of operations. The number of these operations grows in a quadratic
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  5. Trader-friendly stop loss and take profit

    by , 04-17-2024 at 05:23 AM
    Stop loss and take profit are stop orders that close a position when the price reaches their value. Stop loss allows traders to limit losses, while take profit enables thjem to save their gains. The main advantage of using stop loss and take profit is the ability to control financial risks and use money management.
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