Introductory derivations are done before introducing the metric of Fisher’s LDA. Then, after introducing Fisher's LDA and its different forms, Fisher’s Metrics and their maximizations are given. The idea of traces in Fisher's LDA is explained. Weighted features method is used for feature selection. Various simple examples are provided to clarify the idea for the feature selection.