Pattern Recognition: Supervised Learning, Unsupervised Learning, Space (mathematics), Pattern Matching, Feature Extraction, Training Set - Softcover

Buch 1 von 3: Blue Ant
 
9786130492106: Pattern Recognition: Supervised Learning, Unsupervised Learning, Space (mathematics), Pattern Matching, Feature Extraction, Training Set

Inhaltsangabe

Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Pattern recognition is the act of taking in raw data and taking an action based on the category of the pattern". Most research in pattern recognition is about methods for supervised learning and unsupervised learning. Pattern recognition aims to classify data (patterns) based either on a priori knowledge or on statistical information extracted from the patterns. The patterns to be classified are usually groups of measurements or observations, defining points in an appropriate multidimensional space. This is in contrast to pattern matching, where the pattern is rigidly specified. A complete pattern recognition system consists of a sensor that gathers the observations to be classified or described, a feature extraction mechanism that computes numeric or symbolic information from the observations, and a classification or description scheme that does the actual job of classifying or describing observations, relying on the extracted features."

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Reseña del editor

Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Pattern recognition is the act of taking in raw data and taking an action based on the category of the pattern". Most research in pattern recognition is about methods for supervised learning and unsupervised learning. Pattern recognition aims to classify data (patterns) based either on a priori knowledge or on statistical information extracted from the patterns. The patterns to be classified are usually groups of measurements or observations, defining points in an appropriate multidimensional space. This is in contrast to pattern matching, where the pattern is rigidly specified. A complete pattern recognition system consists of a sensor that gathers the observations to be classified or described, a feature extraction mechanism that computes numeric or symbolic information from the observations, and a classification or description scheme that does the actual job of classifying or describing observations, relying on the extracted features."

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