Expert System Expert System is a part of a general category of computer applications known as artificial intelligence. It is describes a computer program that simulates the…
Biodiversity Informatics Biodiversity Informatics provides essential scientific knowledge to better understand global ecosystems and to inform land use and policy decisions. It tends to focus more on…
Speech Recognition Speech Recognition can be defined as the independent, computer‐driven transcription of spoken language into readable text in real time. It is the capability of an…
About Spamming This article focus on Spamming, which is flooding the Internet with many copies of the same message, in an attempt to force the message on…
Machine Learned Ranking 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 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,…
OPTICS Algorithm 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…
Self Organizing Map Self Organizing Map is one of the most popular neural network models. It belongs to the category of competitive learning networks. It is based on…
Information Bottleneck Method This article describe about Information Bottleneck Method, which is a technique in information theory for finding the best tradeoff between accuracy and complexity. Optimal temporal…
Decision Tree Learning Decision Tree Learning is one of the most successful techniques for supervised classification learning. It is one of the most widely used and practical methods…
About Perceptron Perceptron is intended to be a machine, rather than a program, and while its first implementation was in software for the IBM 704, it is…
Random Forest Random Forest can flexibly incorporate missing data in the predictor variables. When missing data are encountered for a particular observation during model building, the prediction…