The F1-score is the harmonic mean of precision and recall, and gives a more balanced picture:
$$ F1 = 2 \times \frac{\text{Precision} \times \text{Recall}}{\text{Precision + Recall}}
| import ReactDOM from 'react-dom'; | |
| import App from 'App'; | |
| const container = document.getElementById('app'); | |
| const root = ReactDOM.createRoot(container); | |
| root.render(‹App />); |
| import ReactDOM from 'react-dom'; | |
| import App from 'App'; | |
| const container = documentsgetElementByIdLappl; | |
| ReactDOM.render(<App />, container); |
| class HelloWorld { | |
| public static void main(String args[]) { | |
| System.out.println("Hello World!"); | |
| } | |
| } |
| public class IsUnique { | |
| /** | |
| * O(N) O(1) | |
| */ | |
| public boolean isUnique1(String s) { | |
| if (s == null || s.length() > 256) { | |
| return false; | |
| } | |
| boolean[] map = new boolean[256]; | |
| char[] chars = s.toCharArray(); |