Aug 28, 2022 · While digging in the details of classical classification methods, I found sparse information about the similarities and differences of Gaussian Naive Bayes (GNB), Linear …

Linear Discriminant Analysis (LDA)# Strategy: Instead of estimating \(P(Y\mid X)\) directly, we could estimate: \(\hat P(X \mid Y)\): Given the response, what is the distribution of the inputs. …

朴素贝叶斯分类器时一种以假设特征相互独立下运用 贝叶斯定理 的简单概率分类器，这里最关键的假设就是 特征相互独立， 这在实际当中几乎是不可能的，在我们所有观测到的特征，基本 …

Linear discriminant analysis (LDA), normal discriminant analysis (NDA), canonical variates analysis (CVA), or discriminant function analysis is a generalization of Fisher's linear …

Jun 5, 2017 · Using Naive Bayes we assume the features to be independent and by using LDA we assume the covariance to be same for all the classes. How does these assumptions make …

Sep 24, 2021 · If you consider the naive Bayes classifier with the assumption of Gaussian distributions and the same variance for different groups/classes, then you could see this as a …

Nov 27, 2023 · Linear discriminant analysis, also known as normal discriminant analysis (NDA) or discriminant function analysis (DFA), follows a generative model framework. This means LDA …

Feb 16, 2017 · I LDA, QDA, Naive Bayes. Generative Models + Can be used to generate data (Pr[X]) + O•ers more insights into data O†en works worse, particularly when assumptions are …

Linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) are model-based methods for classification. LDA and QDA models start with the assumption that the conditional …

Dec 21, 2020 · I know that Bayes’ theorem states that P (A|B) = P (A)P (B|A) / P (B). I do not understand why he uses that expression for P (B) In terms of your example, πk π k is P (A) …