Regularized Composite ReLU-ReHU Loss Minimization with Linear Computation and Linear Convergence
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Updated
Dec 7, 2023
Regularized Composite ReLU-ReHU Loss Minimization with Linear Computation and Linear Convergence
Robust estimations from distribution structures: Mean.
Regularization Paths for Huber Loss Regression and Quantile Regression Penalized by Lasso or Elastic-Net
Least Squares and Huber regression via CQPs
Simple 1d robust regression with huber loss in the case of anomalies / outliers
Project where the Linear Regression algorithm is used
This project predicts sunspot activity using an LSTM model for time series data. Built with TensorFlow and Keras, it uses Huber loss for outlier handling and MAE for performance evaluation. The dataset, sourced from Kaggle or SIDC, spans over 270 years of monthly sunspot data.
Support vector machines flexible framework
Coded examples of Different types of Regression with Visualization.
Predicting energy prices based on weather trends using simple regression models.
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