What if plants could speak when they were thirsty? Agriculture, in essence, is a dialog among crops, soil and climate. Yet drought, the most insidious stressor, remains largely silent until its damage ...

In contrast, the decision tree model performed significantly better, establishing clear decision boundaries and achieving high classification accuracy. The decision tree consistently selected Height ...

Abstract Decision tree is an effective supervised learning method for solving classification and regression problems. This article combines the Pearson correlation coefficient with the CART decision ...

ClassificationAlgorithms Comparing the performance of 3 Classification Algorithms; Decision Tree, Random Forest and Support Vector Machine on a dataset.

For example, you might want to predict the sex of a person (male or female) based on their age, state where they live, income and political leaning. There are many other techniques for binary ...

A decision tree is a machine learning technique that can be used for binary classification or multi-class classification. A binary classification problem is one where the goal is to predict the value ...

Repository files navigation #Decision Tree learning algorithm -Run main.py to generate data shown in the report -For the user to perform training, run decision_tree_learning, prune. Then run ...

While Markov Chain Monte Carlo methods are typically used to construct Bayesian Decision Trees, here we provide a deterministic Bayesian Decision Tree algorithm that eliminates the sampling and does ...