Regression is a task of predicting a real value from an unlabeled example. A well-known example of regression is estimating the value of a diamond based on such characteristics as size, weight, color, clarity, etc. The so-called regression metrics are used to assess the accuracy of regression model predictions. Despite similar algorithms, regression metrics are semantically different from similar loss functions. more...
With the advancement of machine learning and artificial intelligence technologies, there is a growing need to optimize processes for working with models. The efficiency of model operation directly depends on the data formats used to represent them. In recent years, several new data types have emerged, specifically designed for working with deep learning models. In this article, we will focus on two such new data formats - float16 and float8, which are beginning to be actively used ...
LDA is a supervised generalization machine learning algorithm that aims to find a linear combination of features that best separates the classes in a dataset. Just like the Principal Component Analysis(PCA), it is a dimension reduction algorithm, These algorithms are a common choice for dimensionality reduction, in this article we are going to compare them and observe in what situation each algorithm works best. We already discussed the PCA in the prior articles of this ...
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 ...
Time series analysis plays an important role not just in supporting fundamental analysis but in very liquid markets like forex, it can be the main driver for decisions on how one is positioned in the markets. Traditional technical indicators have tended to lag the market a lot which has brought them out of favor for most traders, leading to the rise of alternatives perhaps the most predominant of which, at the moment is neural networks. But what about polynomial interpolation? more...
Recent Visitors
Archive
Go to Profile
Mark as Read