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Financial word of the day: Heteroscedasticity — meaning, usage, and why it matters more than ever
Heteroscedasticity describes a situation where risk (variance) changes with the level of a variable. In financial models, ...
Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...
Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...
Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...
Hybrid Quantum-Classical Algorithm for an Integrated Feature Selection and Logistic Regression Model
Abstract: Feature selection is a pivotal step in machine learning, aimed at reducing feature dimensionality and improving model performance. Conventional feature selection methods, typically framed as ...
Abstract: Recently, developed data-driven SINDy-based techniques can identify the dynamic model of serial robots without simplifying assumptions nor pre-knowledge of all kinematics and geometric ...
This project addresses the problem of predicting water levels in fish ponds - a critical factor in aquaculture management. Using Machine Learning, we can: Predict water levels based on environmental ...
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