The visual data mining process, seen in the first part of this two-part article, revealed patterns in four dimensions between cumulative gas well production and independent variables ...

Evolutionary algorithms have emerged as a robust alternative to traditional greedy approaches for decision tree induction. By mimicking the natural selection process, these algorithms iterate over ...

The algorithm of a decision tree can be integrated with other management analysis tools such as Net Present Value and Project Evaluation Review Technique (PERT).

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 ...

However, Decision Trees can be prone to overfitting, which occurs when the algorithm creates a tree that's too complex and fits the training data too closely.

Conclusions: Multiple molecular and clinicopathological variable integrated decision tree algorithms may individually predict the recurrence pattern for NPC. This decision tree algorism provides a ...

"NeuralTree benefits from the accuracy of a neural network and the hardware efficiency of a decision tree algorithm," Shoaran says. "It's the first time we've been able to integrate such a complex ...

The artificial intelligence method was used to optimize an early cancer detection test to ensure high sensitivity and specificity.

There are many other techniques for binary classification, but using a decision tree is very common and the technique is considered a fundamental machine learning skill for data scientists. There are ...