Pattern Recognition

Feature Extraction and Feature Selection Feature Extraction Feature extraction is for creating a new smaller set of features that stills captures most of the useful information. Feature Selection Feature selection …

Linear Discriminant functions Linear Discriminant functions are the basis for the majority of Pattern Recognition techniques. It is a function that maps input features onto a classification space. A dividing …

Likelihood and Maximum Likelihood Method Likelihood Likelihood is the probability that an observation is predicted by the specified model. Maximum Likelihood Maximum likelihood is the maximum probability that an observation …

Analog to Digital – A/D conversion steps The A/D conversion (coding) involves: Sampling: measuring the amplitude values (or function values) at a finite number of positions. Quantization: representing the amplitude values …

Analog to Digital Conversion – needs for A/D conversion A/D conversion is a sampling from the perspective of Pattern Recognition which goal is to gather sensed data from samples and …

Data Reduction is the transformation of data into a corrupted, ordered and simplified form. Classification of Data Reduction techniques Data cube aggregation ➢ Aggregation operations are applied to the data …

Dimension Reduction Dimensionalily Reduction A dimension denotes a measurement of a certain aspect of an object. Other names for dimension are attribute or feature or variable names in a data …

Pattern Recognition tasks and examples Two types of pattern recognition tasks are available. Supervised Pattern Recognition: If training data is available and the model has prior known information. Examples: Fingerprint …

Naive Bayes Classifier is special Naive Bayes Classifier are a family of simple ‘Probabilistic Classifier’ based on applying Bayes Theorem with strong (naive) independence assumptions between the features. It is …

Gaussian Distribution applications Gaussian functions are broadly used in image processing Gaussian distribution is used for various signal processing Gaussian functions are used to define Artificial Neural Network (ANN) Gaussian …