Learning Tree International, Inc., founded in 1974, is an IT training company based in Herndon, Virginia, United States. They offer training for business...

Decision tree learning is a supervised learning approach used in statistics, data mining and machine learning. In this formalism, a classification or regression...

The Learning Tree is a semiautobiographical novel written by Gordon Parks. The Learning Tree is a 1969 drama film based on the book. Learning Tree may...

likely to reach a goal, but are also a popular tool in machine learning. A decision tree is a flowchart-like structure in which each internal node represents...

successful applications of deep learning are computer vision and speech recognition. Decision tree learning uses a decision tree as a predictive model to go...

compression technique in machine learning and search algorithms that reduces the size of decision trees by removing sections of the tree that are non-critical and...

forests is an ensemble learning method for classification, regression and other tasks that works by creating a multitude of decision trees during training....

"Decision Tree Ensemble: Small Heterogeneous is Better Than Large Homogeneous" (PDF). 2008 Seventh International Conference on Machine Learning and Applications...

The International Conference on Machine Learning (ICML) is a leading international academic conference in machine learning. Along with NeurIPS and ICLR...

well as a milestone in machine learning as it uses Monte Carlo tree search with artificial neural networks (a deep learning method) for policy (move selection)...

Applications International Corporation NII NVR Noblis Revature Verisign Learning Tree International United States Geological Survey National Wildlife Federation...

hotel's tenants include the American Management Association, and Learning Tree International; in addition, New York Sports Club was a former tenant. Developer...

Instance-based learning Lazy learning Learning Automata Learning Vector Quantization Logistic Model Tree Minimum message length (decision trees, decision graphs...

The International Conference on Learning Representations (ICLR) is a machine learning conference typically held in late April or early May each year....

boards of GreenState Credit Union, the United Fire Group, and Learning Tree International. She co-authored marketing textbook Know Your Customer: New Approaches...

Transfer learning (TL) is a technique in machine learning (ML) in which knowledge learned from a task is re-used in order to boost performance on a related...

Curriculum learning is a technique in machine learning in which a model is trained on examples of increasing difficulty, where the definition of "difficulty"...

decision tree algorithm is an online machine learning algorithm that outputs a decision tree. Many decision tree methods, such as C4.5, construct a tree using...

In machine learning, deep learning focuses on utilizing multilayered neural networks to perform tasks such as classification, regression, and representation...

in-context learning is temporary. Training models to perform in-context learning can be viewed as a form of meta-learning, or "learning to learn". Self-consistency...

types: Multi-relational decision tree learning (MRDTL) uses a supervised algorithm that is similar to a decision tree. Deep Feature Synthesis uses simpler...

time included DeVry and CBT Systems, as well as Sylvan Learning and Learning Tree International. By 1999, the president of Knowledge Universe was Tom Kalinske...

Q-learning is a reinforcement learning algorithm that trains an agent to assign values to its possible actions based on its current state, without requiring...

Charles X., et al. "Decision trees with minimal costs." Proceedings of the twenty-first international conference on Machine learning. ACM, 2004. Mahé, Pierre;...

In machine learning, normalization is a statistical technique with various applications. There are two main forms of normalization, namely data normalization...

In machine learning (ML), boosting is an ensemble metaheuristic for primarily reducing bias (as opposed to variance). It can also improve the stability...

Self-supervised learning (SSL) is a paradigm in machine learning where a model is trained on a task using the data itself to generate supervisory signals...

In statistics and machine learning, leakage (also known as data leakage or target leakage) is the use of information in the model training process which...

botany, a tree is a perennial plant with an elongated stem, or trunk, usually supporting branches and leaves. In some usages, the definition of a tree may be...

learning, originally developed by Microsoft. It is based on decision tree algorithms and used for ranking, classification and other machine learning tasks...