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Stock market prediction is the act of trying to determine the future value of a company stock or other financial instrument traded on an exchange. The successful prediction of a stock's future price could yield significant profit. The efficient market hypothesis suggests that stock prices reflect all currently available information and any ...
XGBoost. XGBoost [2] (eXtreme Gradient Boosting) is an open-source software library which provides a regularizing gradient boosting framework for C++, Java, Python, [3] R, [4] Julia, [5] Perl, [6] and Scala. It works on Linux, Microsoft Windows, [7] and macOS. [8] From the project description, it aims to provide a "Scalable, Portable and ...
Gradient boosting is a machine learning technique based on boosting in a functional space, where the target is pseudo-residuals rather than the typical residuals used in traditional boosting. It gives a prediction model in the form of an ensemble of weak prediction models, i.e., models that make very few assumptions about the data, which are ...
LightGBM, short for Light Gradient-Boosting Machine, is a free and open-source distributed gradient-boosting framework for machine learning, originally developed by Microsoft. [ 4][ 5] It is based on decision tree algorithms and used for ranking, classification and other machine learning tasks. The development focus is on performance and ...
The Robert H. Herz Stock Index From June 2011 to December 2012, if you bought shares in companies when Robert H. Herz joined the board, and sold them when he left, you would have a -15.2 percent return on your investment, compared to a 8.5 percent return from the S&P 500.
Orange, a free data mining software suite, module Orange.ensemble Weka is a machine learning set of tools that offers variate implementations of boosting algorithms like AdaBoost and LogitBoost R package GBM (Generalized Boosted Regression Models) implements extensions to Freund and Schapire's AdaBoost algorithm and Friedman's gradient boosting ...
Mixture model. In statistics, a mixture model is a probabilistic model for representing the presence of subpopulations within an overall population, without requiring that an observed data set should identify the sub-population to which an individual observation belongs. Formally a mixture model corresponds to the mixture distribution that ...
CatBoost. CatBoost [6] is an open-source software library developed by Yandex. It provides a gradient boosting framework which among other features attempts to solve for Categorical features using a permutation driven alternative compared to the classical algorithm. [7] It works on Linux, Windows, macOS, and is available in Python, [8] R, [9 ...