The algorithm is used to address, among other issues in the recursive partial least-squares (RPLS) regression algorithm, the “forgetting factor” and sensitivity of variable scaling. Two levels of ...

Linear Trees combine the learning ability of Decision Tree with the predictive and explicative power of Linear Models. Like in tree-based algorithms, the data are split according to simple decision ...

In noise-free systems, the recently proposed distributed linear regression algorithm, named the Iteratively Pre-conditioned Gradient-descent (IPG) method, has been claimed to converge faster than ...

The apparent conductivity at different effective depths was used to predict the measured conductivity at different periods and soil depths, and then a multiple linear ... Technical flow chart. In ...

Abstract: The k-vectors algorithm for learning regression functions proposed here is akin to the well-known k-means algorithm. Both algorithms partition the feature space, but unlike the k-means ...

Predicting car prices using multiple linear regression. This project uses real-world automotive data to train a machine learning model capable of estimating car prices based on technical ...