Logistic Regression

Logistic Regression
A more popular solution is to turn to Logistic Regression.

Logistic regression A conditional statistical model of binary variable y given measurement vector x. The probability that y is 1 is given by the logistic function applied to a linear combination of x. That is, p(y=1) = 1/(1+exp(-a*x)).

Logistic regression: -
This form of regression is very similar to the linear regression but is done when the output variable can have only two values (like true/false, 0/1) and the input variable can have any type of value - categorical, ...

General Logistic Regression Model. The general logistic model can be stated as:
y = b0/{1 + b1*exp(b2*x)} ...

Logistic regression, a type of generalized linear regression used for predicting binary or categorical outputs (also known as maximum entropy classifiers)
Linear discriminant analysis
Support vector machines
Boosting
Conditional random fields ...

logistic regression
A linear regression that predicts the proportions of a categorical target variable, such as type of customer, in a population.
multidimensional database ...

6.6.2 Logistic Regression
6.6.3 Logistic Regression: Classification
6.6.4 Advanced: Learning in Logistic Regression ...

My brief rejoinder: the residuals of a logistic regression to predict the presence of Diebold machines based on Clinton Campaign presence, median age, % holding bachelor's degrees, percapita income, ...

Discriminant Function Analysis from StatSoft
Discriminant tutorial Using SPSS with FAQ
Logistic regression and discriminant analysis using SPSS code
Technical Papers ...

compared the prediction of survival of neural networks and logistic regression models on alcoholic patients with severe liver disease. The study reveals that neural networks were more successful in classifying patients into low and high-risk group.

A single-layer neural network can compute a continuous output instead of a step function. A common choice is the so-called logistic function, 1/(1+exp(-x)). With this choice, the single-layer network is identical to the logistic regression model, ...

Its technical focus is on decision support, knowledge-based systems (qualitative and quantitative), learning systems (including logistic regression, classification trees, neural networks, rough sets), ...

See also: Regression, Classification, Neural network, Distribution, Validation