A classifier is said to be a piecewise linear machine if its discriminant functions linear machine have the form Where (a) Indicate how a piecewise linear machine can be viewed in terms of a linear machine for classifying subclasses of patterns. (b) Show that the decision regions of a piecewise linear machine can be nonconvex and even multiply connected. (c) Sketch a plot of gij (x) for a one-dimensional example in which n1 = 2 and n2 = 1 to illustrate your answer to part (b).
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
A classifier is said to be a piecewise linear machine if its discriminant functions linear machine have the form
Where
(a) Indicate how a piecewise linear machine can be viewed in terms of a linear machine for classifying subclasses of patterns.
(b) Show that the decision regions of a piecewise linear machine can be nonconvex and even multiply connected.
(c) Sketch a plot of gij (x) for a one-dimensional example in which n1 = 2 and n2 = 1 to illustrate your answer to part (b).