5 Alternative methods Besides trimming and winsorizing, there are other methods to deal with outliers in regression, such as transforming the data, using robust estimators, or adding dummy variables.

A novel framework has recently been proposed for designing the molecular structure of chemical compounds with a desired chemical property using both artificial neural networks and mixed integer linear ...

Proactive strategies to prevent summer learning loss can help reduce the achievement gap that often widens during summer months.

A meta-analysis of 47 published cases of hypocalcaemia and cardiac dysfunction used univariate linear regression analysis to demonstrate that both QT interval and left ventricular ejection fraction ...

What Are Autoregressive Models? Autoregressive models are statistical models used for time series analysis, where current values are predicted based on a linear combination of past values. These ...

The demo creates a linear support vector regression model, evaluates the model accuracy on the training and test data, and then uses the model to predict the target y value for x = [-0.1660, 0.4406, ...

The final predictions are the sum of the raw linear predictions and the residuals modeled by the Random Forest. Linear Boosting is a two stage learning process. Firstly, a linear model is trained on ...

Combining these results lead to the proposed Adaptive Optimizable Gaussian Process Regression Linear Least Squares Regression (AO-GPRLLSR) Filtering pipeline. The AO-GPRLLSR method generated an ...