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# 2BASE CLASSIFIERS

The classifiers whose decisions are combined to form the ensemble are called “base classifiers.” This chapter details some of the most popular base classifier models.

## 2.1 LINEAR AND QUADRATIC CLASSIFIERS

### 2.1.1 Linear Discriminant Classifier

Linear and quadratic classifiers are named after the type of discriminant functions they use. Let be the object to classify in one of c classes. Let be a vector with coefficients and wi0 be a constant free term. A linear classifier is any set of c linear functions, one for each class, , i = 1, …, c,

(2.1) The tag of the largest gi(x) determines the class label.

#### 2.1.1.1 Training Linear Discriminant Classifier.

A straightforward way to train a linear discriminant classifier (LDC) is shown in Figure 2.2 and detailed below:

1. Estimate the prior probabilities for the classes. Let Ni be the number of objects in the data set Z from class ωi, i = 1, …c, and yj ∈ Ω be the class label of zjZ. Then
(2.2) 2. Calculate estimates of ...

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