Sage-Tips

What is the difference between logistic regression and the discriminant analysis?

While both are appropriate for the development of linear classification models, linear discriminant analysis makes more assumptions about the underlying data. Hence, it is assumed that logistic regression is the more flexible and more robust method in case of violations of these assumptions.

Are LDA and logistic regression similar?

Because logistic regression relies on fewer assumptions, it seems to be more robust to the non-Gaussian type of data. In practice, logistic regression and LDA often give similar results.

Which is better LDA or logistic regression?

LDA assumes that the observations are drawn from a Gaussian distribution with a common covariance matrix in each class, and so can provide some improvements over logistic regression when this assumption approximately holds. Conversely, logistic regression can outperform LDA if these Gaussian assumptions are not met.

Is LDA logistic regression?

Linear discriminant analysis (LDA) and logistic regression (LR) are often used for the purpose of classifying populations or groups using a set of predictor variables. The performance of LDA was also tested by using various prior probabilities.

Which is better LDA or Qda?

LDA (Linear Discriminant Analysis) is used when a linear boundary is required between classifiers and QDA (Quadratic Discriminant Analysis) is used to find a non-linear boundary between classifiers. LDA and QDA work better when the response classes are separable and distribution of X=x for all class is normal.

Is discriminant analysis regression based?

In many ways, discriminant analysis parallels multiple regression analysis. The main difference between these two techniques is that regression analysis deals with a continuous dependent variable, while discriminant analysis must have a discrete dependent variable.

What is difference between multiple regression and logistic regression?

Simple logistic regression analysis refers to the regression application with one dichotomous outcome and one independent variable; multiple logistic regression analysis applies when there is a single dichotomous outcome and more than one independent variable.

How do you do discriminant analysis?

Discriminant analysis is a 7-step procedure.

1. Step 1: Collect training data.
2. Step 2: Prior Probabilities.
3. Step 3: Bartlett’s test.
4. Step 4: Estimate the parameters of the conditional probability density functions f ( X | π i ) .
5. Step 5: Compute discriminant functions.

How many methods are there in discriminant analysis?

Methods implemented in this area are Multiple Discriminant Analysis, Fisher’s Linear Discriminant Analysis, and K-Nearest Neighbours Discriminant Analysis. (MDA) is also termed Discriminant Factor Analysis and Canonical Discriminant Analysis.

What is the difference between regression and discriminant analysis?

Regression is done on data which has independent variables which are on ordinal scale. Whereas Discriminant analysis is done when the dependent variables have categorical data and independent variables are measured on a Likert scale.

When do we use logistic regression?

Logistic regression is often used when we aren’t even interested in categorization but in getting the odds ratios for each variable. Both of the analysis method used when dependent variable is a categorical variable.

What is the difference between LDA and logistic regression?

In LDA, the groups should be roughly equal in size, in logistic reg. that is not necessary. It may have slightly greater power than logistic regression when the assumptions are met, but, these days with large data sets, that is less and less of an issue. For details see e.g. Pohar et al [ 1] and this thread on cross validated [ 2].

What is the difference between DFA and LR in regression analysis?

LOGISTIC REGRESSION (LR): While logistic regression is very similar to discriminant function analysis, the primary question addressed by LR is “How likely is the case to belong to each group (DV)”. In contrast, the primary question addressed by DFA is “Which group (DV) is the case most likely to belong to”.