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For a few time-series, it is possible to devise a formula for the next value in the sequences basing off of previous values that appeared within it. Number walls allow this to be accomplished by preliminarily generating a ‘wall of numbers’, in the form of a matrix via what is referred to as the cross-rule. In generating this matrix, the primary goal is to establish if the sequence in question is convergent and the number wall cross rule algorithm gladly answers this question, if after a few rows ...
Adaboost, short for adaptive boosting is an ensemble machine learning model that attempts to build a strong classifier out of weak classifiers. more...
Support Vector Regression (SVR) is a form of regression derived from Support Vector Machines. At its core, SVR uses kernel methods to map input data into higher-dimensional spaces, allowing for more complex relationships to be captured, which contrasts with dimensionality reduction. For this article though we are exploring strictly its loss function role when used with a multi-layer perceptron. A related but different form of regression we looked at in an earlier article was Gaussian Process ...
According to Wikipedia, Dimensionality Reduction is the transformation of data from a high-dimensional space into a low dimensional space so that the low-dimensional representation retains some meaningful properties of the original data, ideally close to its intrinsic dimension. more...
The financial markets industry is a complex and multifaceted environment. Every event and action have their roots in economic fundamental processes. The reason for certain events can be found in the news, geopolitical events, various technical aspects and many other factors. Quite often, we observe such dependencies after they happen. While analyzing the market situation, we observe only a small part of these factors. This in general makes financial markets a rather difficult environment ...
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