Decision tree is one of the models that are often used in classification. Pruning is necessary for decision tree in order to prevent overfitting. With the advent of the era of big data, there is one ...

Data mining or Knowledge discovery is seen as an increasingly important tool by modern business to transform data into an informational advantage. Mining is a process of finding correlations among ...

DecisionTrees can be fairly sensitive to the data used for training. This often leads to overfitting, but with the GeneticDecisionTree, we take advantage of this to generate random candidate models ...

Dtree - A simple pure-Python decision tree construction algorithm Overview Given a training data set, it constructs a decision tree for classification or regression in a single batch or incrementally.

Decision Tree is the simple but powerful classification algorithm of machine learning where a tree or graph-like structure is constructed to display algorithms and reach possible consequences of a ...

"Jump discontinuities" in visual plots led to use of data mining decision trees as an ideal form of analysis useful in obtaining a profit exploration pattern from the British Columbia database.

The Data Science Lab Binary Classification Using a scikit Decision Tree Dr. James McCaffrey of Microsoft Research says decision trees are useful for relatively small datasets and when the trained ...

Decision trees, such as C4.5 (ref. 1), CART 2 and newer variants, are classifiers that predict class labels for data items.

Some of the most common classification algorithms are logistic regression, decision trees, support vector machines, k-nearest neighbors, and neural networks.