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Machine Learned Ranking is useful for many applications in Information Retrieval, Natural Language Processing, and Data Mining. It refers to machine learning techniques for training the model…

Handwriting Recognition is known as optical character recognition (OCR), which is the most successful in the mainstream. Most scanning suites offer some form of OCR,…

Quantitative Structure-Activity Relationship is based on the observation that the structures of active small molecules and the resulting molecular properties are directly related to biological…

Supervised Learning is the machine learning, which is to build a model that makes predictions based on evidence in the presence of uncertainty. As adaptive…

This article talks about Q-Learning, which learns the optimal policy even when actions are selected according to a more exploratory or even random policy. It…

Deep Learning is a term that covers a particular approach to building and training neural networks. It is part of a broader family of machine…

Temporal Difference Learning is an unsupervised technique in which the learning agent learns to predict the expected value of a variable occurring at the end…

This article describe about Reinforcement Learning, which differs from standard supervised learning in that correct input/output pairs are never presented, nor sub-optimal actions explicitly corrected.…

Semi Supervised Learning involves function estimation on labeled and unlabeled data. This approach is motivated by the fact that labeled data is often costly to…

Local Outlier Factor (LOF) is based on a concept of a local density. Local density is estimated by the typical distance at which a point…

This article talks about Ordering Points to Identify the Clustering Structure (OPTICS), which is not a clustering technique per se as it does not output…

Density Based Spatial Clustering of Applications with Noise (DBSCAN) can identify clusters in large spatial data sets by looking at the local density of database…