Machine Learning through Regression Trees on Crimes Data In this lab you will learn how to implement regression trees using ScikitLearn. We will show what parameters are important, how to train a ...

Decision tree regression is a machine learning technique . To predict the output y for an input vector X, the tree structure encodes a set of if-then rules such as, "If the value of X at index [2] is ...

The terrestrial water storage anomaly (TWSA) from the previous Gravity Recovery and Climate Experiment (GRACE) covers a relatively short period (15 years) with several missing periods. This study ...

This repository contains R code for implementing kernel regression tree and its comparison between boosting, random forest and KNN predictions in both simulated data and real data. Regression trees ...

The goal of a machine learning regression problem is to predict a single numeric value. For example, you might want to predict the annual income of a person based on their sex (male or female), age, ...

A tree-based method for regression is proposed. In a high dimensional feature space, the method has the ability to adapt to the lower intrinsic dimension of data if the data possess such a property so ...